Welcome to the 2023 Research Projects page.
Anthropology
ANT-01: What Causes Diabetes Myelitis Among Young Americans?
Primary mentor: Prof. Amarasiri De Silva
UCSC faculty contact: Prof. Mary Beth Pudup
Location: 100% remote and online
Number of interns: 3
Project description:
This research project involves a learning activity known as qualitative research in anthropology. The interview data in this research project focus on people’s perception of diabetes problems, especially why young Americans get diabetes. The project will provide training on interviewing skills at the beginning. The mentor will train the SIP interns to collect and analyze interview data from the communities close to the interns. The interview data will be collected using audio scripts, notes, or both. The mentor will discuss the tools that are used for data collection, and the interns will be trained to use these tools. Data coding and analysis will be done using a textual data analysis program called Atlas/Ti. The SIP interns who are interested in video making will be encouraged to document the interview process and the key factors emerging from the interview.
Tasks:
In this research project on diabetes among young people in California, the SIP mentor and interns will do interviews with individuals to find out about how young people got affected with diabetes mellitus. The interns will do in-person interviews, conduct video chats, and collect data using social media such as WhatsApp, and Google searches. The interns will also collect literature on the subject, review these materials, and write short statements on the findings. The interns will be trained to do qualitative data analysis. The interns’ end-of-program presentation will be an essay based on their collected data.
Required skills for interns prior to acceptance: None
ANT-02: Tragic Technology Layoff and the Non-Immigrant Indian Diaspora
Primary mentors: Prof. Annapurna Devi Pandey, Urvi Vyas
Location: 100% remote and online
Number of interns: 5
Project description:
The Indian diaspora, one of the most vibrant and dynamic, is the largest in the world, with 18 million people from the country living outside their homeland in 2020. There are about 4.2 million Indians in the US, and the community is known for its diversity in terms of language, religion, region, class, caste, gender, and sexuality. Today, Indian Americans are a mosaic of recent arrivals and long-term residents. While most are immigrants, a rising share is born and raised in the United States. Many Indian immigrants have brought with them identities rooted in their ancestral homeland, while others have eschewed them in favor of a non-hyphenated “American” identity. Despite the overall professional, educational, and financial success many Indian Americans enjoy, this has not innoculated them from the forces of discrimination, polarization, and contestation over questions of belonging and identity. How do the vastly diverse groups of Indian Americans perceive their own ethnic identity? How do they respond to the dual impulses of assimilation and integration? How might their self-conception influence the composition of their social networks?
Tasks:
In this research project, the SIP mentor and SIP interns will collect stories about the recent tech layoff on the specific visa holders from India, e.g., H-1B and H-4 types. In this research project, the SIP interns will collect personal stories of the experiences of the Indians on H-1B and H-4 visas by using in-person interviews, video chats, LinkedIn, WhatsApp, and Zoom. The interns will interview recruiters, entrepreneurs, and tech specialists and will do a review of literature on the subject. The interns will create a digital story for their final presentation.
Required skills for interns prior to acceptance: None
Applied Artificial Intelligence
AAI-01: UNet and GANs in Medical Images
Primary mentor: Nahid Nasiri
UCSC faculty contact: Prof. Gabriel Elkaim
Location: 100% remote and online
Number of interns: 3
Project description:
UNet is a convolutional neural network architecture that expanded with few changes in the CNN architecture. It was invented to deal with biomedical images where the target is not only to classify whether there is an infection or not but also to identify the area of infection. On the other hand, medical images suffer from lack of enough images for deep learning purposes. To compensate this problem, we will study Generative Adversarial Networks (GANs) which is one of the vital efficient methods for generating a massive, high-quality artificial picture. GANs is a class of generative models that was introduced by Goodfellow et al. It is one of the most-cited papers in computer science (nearly 26000 at the time of writing of this proposal), which proves this method’s popularity and importance in the machine learning and deep learning fields. Yann LeCun, who is a pioneer in the modern revolution in deep neural networks, declared GANs as “the most interesting idea in the last 10 years in machine learning.” For diagnosing particular diseases in a medical image, a general problem is that it is expensive, usage of high radiation dosage, and time-consuming to collect data. Hence GAN is a deep learning method that has been developed for the image to image translation, i.e. from low-resolution to high-resolution image, for example generating Magnetic resonance image (MRI) from computed tomography image (CT).
Tasks:
The SIP interns’ tasks will include: (1) Python programming every week; (2) machine learning frameworks such as TensorFlow and Keras; (3) data collection and augmentation; (4) the most advanced topics in deep learning — i.e., UNet and GANs; (5) critical reading of research papers; and (6) being familiar with machine learning for medical purposes.
Required skills for interns prior to acceptance: Computer programming
AAI-02: Behavior Modeling with Reinforcement Learning
Primary mentor: Golam Md Muktadir
UCSC faculty contact: Prof. Jim Whitehead
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Reinforcement Learning (RL) is a subdomain of Machine Learning (ML), where intelligence is learned without supervision. RL has successfully been applied in robotics, finance, design, etc. In the mentor’s research, RL is used to model human behavior for simulation.
Tasks:
The SIP interns will learn some algorithms and applying them in real-world experiments.
Required skills for interns prior to acceptance: Computer programming
AAI-03: Artificial Intelligence in Self-Driving Cars
Primary mentor: Majid Moghadam
UCSC faculty contact: Prof. Gabriel Elkaim
Location: 100% remote and online
Number of interns: 4
Project description:
Self-driving cars use a stack of multiple sensors to observe the environment and make decisions. Artificial intelligence algorithms in recent years have helped these vehicles to improve their intelligence significantly. In this research project, the SIP interns will learn how self-driving cars see, think, and take actions using AI algorithms. The interns will involve in simple Python programming tasks to build an AI agent that plays a game just like humans do.
Tasks:
The SIP interns will: (1) learn about how self-driving cars observe, make decisions, and take actions; (2) learn about the basics of Deep Reinforcement Learning algorithms; (3) get hands on Python programming; (4) create simple game environments in Python; (5) train Reinforcement Learning algorithms for a small game in Python; and (6) learn how Deep Reinforcement Learning algorithms can be used on self-driving cars to make decisions. The interns will need access to a laptop for this research project.
Required skills for interns prior to acceptance: Computer programming
AAI-04: Applications with ChatGPT
Primary mentor: Brian Mak
UCSC faculty contact: Prof. Jeff Flanigan
Location: 100% remote and online
Number of interns: 3
Project description:
ChatGPT has taken the world by storm in the past few months, making an impact on culture and providing services to everyday people that no AI model has done before. From content creation, to drafting emails, to helping people write their code, ChatGPT has become an essential tool for the modern era in the blink of an eye. In this research project, the SIP mentor and interns will introduce concepts underlying how and why ChatGPT works, as well as how to access it in a programmatic way using Python.
Tasks:
With guidance from the mentor, the SIP interns will design and implement an application using ChatGPT as a backend. The interns will learn about the strengths and limitations of modern NLP models, and the ideas and mathematics that power them. The interns will also learn the programming skills needed to effectively deploy them like Python, the OpenAI api, Unix/Shell scripting, and git version control.
Required skills for interns prior to acceptance: None
URL: https://jflanigan.github.io/
AAI-05: Autoencoders in Space Optical Communications
Primary mentors: Abdulaziz Alatawi, Abdo Fikky
UCSC faculty contact: Prof. Zouheir Rezki
Location: In person/hybrid on the UCSC campus
Number of interns: 4
Project description:
Autoencoders are neural networks that can learn a compressed representation of the input data, called the latent code, through unsupervised learning. This code is a summary or compression of the input that can be used for a variety of tasks, such as image generation, anomaly detection, and dimensionality reduction. This research project focuses on autoencoders. The SIP interns will use Python libraries like PyTorch and TensorFlow to study research papers and reproduce results. This will help the interns gain practical experience in implementing end-to-end performance systems in wireless communication systems and understand other applications of autoencoders. Additionally, the interns will receive a good introduction to the Python programming language and space optical wireless communications. The SIP interns will periodically present their progress to ensure a good learning process.
Tasks:
To start, the SIP interns will receive a specific schedule for the first two weeks to learn Python programming. The coursework will entail completing exercises, watching videos, and receiving a comprehensive introduction to wireless communications. Additionally, the interns will be asked to submit daily progress reports on their assigned tasks. The interns will also be required to read the mentors’ published GLOBECOM paper to understand the system model right from the beginning.
Starting in week #3, the SIP interns will be taught how to implement autoencoders in wireless communications and create plots for (Bit Error Rate) BER results and constellation diagrams presented in the GLOBECOM paper. Through reading technical papers, the interns will focus on improving the published research work by introducing security constraints and improving BER results compared to state-of-the-art models. In addition, the interns will explore different fading channel scenarios and develop a system that can function effectively not only in specific channel conditions but also in various channel scenarios. Additionally, it would be valuable to compare the proposed autoencoder solutions for various channel conditions with the federated learning approach.
Required skills for interns prior to acceptance: None
AAI-06: Autonomous Driving and Human+AI Team Up
Primary mentors: Vanshika Vats
UCSC faculty contact: Prof. James Davis
Location: 100% remote and online
Number of interns: 3
Project description:
The autonomous driving (AD) domain has made a significant progress in the last few years, taking help of a network of sensors to collect information about the surroundings and make decisions. However, there is a long way to go and a long time before we see completely automated self-driving vehicles (SDVs), as we cannot afford to have them make mistakes when the people’s lives are at stake. Given the fact that humans are more rational in making these complex decisions, incorporating human intelligence can greatly benefit the decision making of SDVs.
Tasks:
In this research project, the SIP interns will learn about how an AD vehicle “sees” and “senses” its environment, which leads to the formation of multiple advanced driver assistance system (ADAS) features, and will explore how humans can contribute to the whole AI pipeline. The interns will spend the first two weeks learning about the basics of AD and how one collects and processes data from different sensors. The concept of machine learning will be introduced and how it is used to make decisions in autonomous vehicles. The mentor and interns will then brainstorm about incorporating human intelligence in AD. The SIP interns will be asked to come up with various ideas for human+AI team up followed by discussions and feedback sessions.
Required skills for interns prior to acceptance: None
URL: https://sites.google.com/ucsc.edu/vis/
AAI-07: Human-in-the-Loop in Autonomous Vehicle Object Recognition
Primary mentors: Marzia Binta Nizam
UCSC faculty contact: Prof. James Davis
Location: 100% remote and online
Number of interns: 3
Project description:
The goal of this research project is to investigate if human computation can improve the accuracy of object recognition algorithms in autonomous driving systems. Object recognition is a critical component of autonomous driving systems, as it enables the vehicle to identify and respond appropriately to objects in its environment such as other vehicles, pedestrians, and obstacles.
Tasks:
In this research project, the SIP interns will design experiments to test the accuracy of object recognition algorithms in autonomous vehicles with and without human input. Human computation can involve tasks such as labeling images, identifying objects in real-time video streams, or providing feedback on the accuracy of the algorithms. The interns will then compare the results of these experiments to determine if human computation improves the accuracy of the object recognition algorithms in autonomous vehicles. The interns will also investigate the effectiveness of using crowdsourcing to annotate data for machine learning algorithms. The interns will compare the results of crowdsourced data annotation to expert annotation and explore the impact of different factors such as task design, incentives, and quality control on the accuracy of crowdsourced data annotation.
Required skills for interns prior to acceptance: None
Art, Culture, and STEM
ACS-01: Art and Science: Visual Storytelling Through Archives, Research, and Design
Primary mentor: Saul Villegas
UCSC faculty contact: Prof. Jennifer Parker
Location: 100% remote and online
Number of interns: 3
Project description:
This research project is designed to provide students with an in-depth look at the environmental issues facing California’s Central Valley. Through the use of digital tools, the SIP interns will explore the scientific, artistic, and cultural aspects of the region’s unique environment. The interns will learn about the area’s natural resources, the impact of human activity, and the current efforts to protect and conserve these resources. The project will incorporate research and digital world-building to give the interns an up-close look at the region’s unique flora and fauna. Additionally, the interns will learn the basics of digital media production to create their own projects that address a unique approach to creative research processes. Through this research project, the SIP interns will develop an appreciation for the environment and its role in the lives of all living organisms. At the conclusion of the research project, the interns will produce a final exhibition of their works, providing an interactive platform to engage with the Central Valley’s ecology.
Tasks:
The SIP interns will develop research assets such as speculative design and learn to create digital assets for virtual 3D world-building to be viewed on a computer browser, phone, or tablet. Speculative design, sometimes called critical design or design fiction, asks us to zoom out beyond user-centered design and ask what the effects of our designs could be on future societies. Outcomes from this research will be published as a virtual exhibition through the OpenLab Collaborative Research Center. Creating a virtual hub on Mozilla Spoke will allow for active participation in exhibiting their research for a diverse community while investigating virtual spaces that reimagine the cultivation practices as both sustainable and not sustainable.
Required skills for interns prior to acceptance: None
URL: https://www.modernobysaulvillegas.com/
ACS-02: Visualizing Plastic: Arts-Based Research on Microscopic Pollution
Primary mentor: Annika Berry
UCSC faculty contact: Prof. Jennifer Parker
Location: 100% remote and online
Number of interns: 3
Project description:
What comes to mind when we hear “plastic pollution”? Water bottles washed onto beaches, overflowing trash bins, litter on the side of the road? In this research project, the SIP mentor and SIP interns will zoom in to consider plastic pollution on a microscopic scale, as it exists across our food chains, bloodstreams, endocrine systems, and as a sedimentary layer in our fossil record. Using digital tools, including AI image generation and animation techniques, the research group will explore new ways to visualize, confront, and communicate the accumulation of micro and nanoplastics in our environment. The SIP interns will learn how to conduct research, develop a story, write a script, create digital assets, and learn image and animation techniques and editing processes to communicate science to larger public audiences.
Tasks:
The SIP interns will conduct research, develop a story, write a script, create digital assets, learn image-production and animation workflows, experiment with AI visualization tools, and utilize Adobe Suite Programs.
Required skills for interns prior to acceptance: None
URL: https://openlabresearch.com
ACS-03: The Spaces in Between
Primary mentors: Prof. José Carlos Espinel, Prof. Raja GuhaThakurta
UCSC faculty contact: Prof. Jennifer Parker
Location: In person/hybrid on the UCSC campus
Number of interns: 11
Project description:
This interdisciplinary research project will explore storytelling in the visual arts through a variety of media including pencil drawing, pen and ink, reliefs, sculpture, and 3D printing. The storytelling aspect of the project will be just as important, if not more important, than techniques and execution. The process of 3D modeling through the computer, which will be explored with Prof. Espinel, will open up a vast universe of creative options. These models will later be printed through different systems and materials, and will provide the SIP interns with technical as well as analytical skills that will be key in the near future. The pencil/pen-and-ink drawing technique that the SIP interns on this project will explore with Prof. GuhaThakurta is the use of a “substrate” of handwritten/hand drawn words/phrases, thematic patterns, symbols, and/or mini drawings to create the shading that will make the image appear realistic when viewed from a distance.
Tasks:
Each SIP intern on this project will be expected to create at least a few (and perhaps several) pieces of 2D and 3D art in the course of the eight weeks of the summer program. 3D pieces will be related to the topic “life beyond earth”, which will be discussed in group meeting and the mentors will let the interns imagine new ways of life. The SIP interns will be expected to design and create three to seven 3D models, including reliefs and sculptures. The interns will also create 2D artworks featuring their 3D models (3D rendering of still image or video). They will 3D-print one to three 3D models. Finally, each 2D pencil drawing, pen and ink, and/or other dry or paint media art piece will be based on a personal theme, topic, and/or event of the intern’s choosing.
Required skills for interns prior to acceptance: None
URL: www.ucm.es/jcespinel ; https://www.ucolick.org/~raja/art/
ACS-04: Gender, Cyberspace, and Art Practice
Primary mentors: Jingtian Zong
UCSC faculty contact: Prof. Jennifer Parker
Location: 100% remote and online
Number of interns: 5
Project description:
This research project examines the complex relationship between gender and cyberspace, following the early spirit of cyberfeminism. Could we escape gender in a virtual space? How do gender and the Internet shape each other? How does contemporary technology enable and, sometime, hinder revolutionary changes? Drawing inspiration from historical and recent cyberfeminism theories and practices, the SIP interns will learn how to conduct research and address their own understanding of gender and cyberspace through web art, audiovisuals, and other digital mediums.
Tasks:
The SIP interns will:
- Conduct research on topics including but not limited to cyberfeminism, gender identity, and online censorship in their own chosen cultural context;
- Make individual digital art projects (web art, audiovisuals, games, etc.) to address issues around gender and cyberspace; and
- Build a collective archive of the research and/or a platform to display the outcome art pieces.
Required skills for interns prior to acceptance: None
URL: https://openlabresearch.com/
ACS-05: Computational Narrative Cinema
Primary mentor: Allen Riley
UCSC faculty contact: Prof. Rick Prelinger
Location: 100% remote and online
Number of interns: 3 + TSIP
Project description:
This research project will be a good fit for SIP/TSIP interns who are interested in art and technology. During the summer, the interns will work together in a studio setting and learn how to use tools such as large language models, computer-controlled cameras and video mixers, and command-line video editing to create videos with a narrative storyline. The SIP mentor and interns will explore a science fiction premise that presents a fantastical reimagining of the history and future of communication technology, and will research and adapt methods from conceptual art, Fluxus, and social practice art. By doing so, the research group will examine how art can be used as a means of social critique and collaboration.
Tasks:
The SIP/TSIP interns will develop skills in media production, collaboration, and critical thinking by reflecting on these representations of technology and engaging in collaborative, computationally-assisted video production. The research project will emphasize the importance of technical skills and imaginative narrative storytelling, as well as the role of activity design and participation derived from contemporary art practices.
Required skills for interns prior to acceptance: None
Astronomy and Astrophysics
AST-01: Comparison of Spec2D vs. PypeIt
Primary mentors: Shreyanshi Garg, Chien-Chu (Charity) Wei
Secondary mentor: Dr. Lara Cullinane
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: In person/hybrid on the UCSC campus
Number of interns: 6
Project description:
Astronomical spectra are measured with the help of a spectrograph. Specifically, the mentor’s research group mostly uses the DEIMOS instrument on the Keck II 10-meter telescope on the summit of Maunakea on the Big Island of Hawaii. A spectrum spreads a star’s light out using something similar to a prism, and then takes a picture of that spread out light. The tricky bit comes from turning that CCD picture, which just shows the number of photon counts in each pixel, into something that one can use scientifically. Astronomers generally use data reduction packages to do this, but something they are interested in studying is how different the results from different data reduction packages are. Such a comparison will be the focus of this research project, and is important not only for the mentor’s research group, but for the broader astronomy community that relies on the results of these spectroscopic data reduction pipelines.
Tasks:
For the most part, the mentor’s research group uses spectroscopic data that have been reduced using an older IDL-based software package called Spec2D, which produces 1D spectra but doesn’t the user give much insight into the intermediate stages of the data reduction process. The exciting revolution over the last few years has come with the development of the newer, more user friendly, Python-based code, PypeIt. The mentors would like the SIP interns to help the group answer and address the following questions:
(1) How different are the output 1D spectra from Spec2D vs. PypeIt?
(2) If they are different, which data reduction package is doing a better job of extracting spectra?
(3) What are the main limitations/problems that one runs into with 1D spectra that have been reduced using PypeIt? (the mentor’s group has a good sense of the data reduction problems associated with Spec2D, but don’t know what these are for PypeIt)
(4) Once the research group better understands output 1D spectra from PypeIt, they would like to go back through all of their data collected over the last two decades, and re-reduce them using PypeIt.
Required skills for interns prior to acceptance: None
URL: https://pypeit.readthedocs.io/en/latest/cookbook.html, https://app.ubinum.com/lab/raja-uco-lick-observatory
AST-02: What Happens Around Supermassive Black Holes
Primary mentor: Prof. Martin Gaskell
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Astronomers now believe that every large galaxy contains a supermassive black hole in its center. Because of the tremendous energy released as the black hole grows by swallowing gas, these black holes can be readily detected as so-called “active galactic nuclei” (AGNs) back to very early times in the Universe. The details of how supermassive black holes form and grow and how this is related to the formation of normal galaxies is one of the central mysteries of contemporary astrophysics. The mentor’s research group is analyzing spectra and spectral variability to try to understand how AGNs produce the intense radiation seen, what the structure of material around the black hole is like, and how supermassive black holes grow.
Tasks:
The SIP interns will analyze multi-wavelength data taken from X-ray and ultraviolet satellites together with data taken from ground-based telescopes. The interns will compare these emissions with theoretical models and study how they vary with time. The SIP interns should have a laptop (PC preferred) with an external mouse and Microsoft Excel installed on the laptop.
Required skills for interns prior to acceptance: None
URL: https://www.astro.ucsc.edu/faculty/index.php?uid=mgaskell
AST-03: How Often Do Quasars Masquerade as RR Lyrae Candidates in Time Domain Photometric Surveys
Primary mentor: Kayla Bartel
Secondary mentor: Yuting Feng
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: 100% remote and online
Number of interns: 3
Project description:
It was long thought that galaxies are so-called “island universes.” Recently, however, more and more distant stars have been discovered in the halo of our Milky Way galaxy, and their distance suggests that the halos of galaxies are much larger than previously thought, implying that galaxies in our Local Group are comparable in size to the typical distance between them. These distant stars are a particular class of variable stars called RR Lyrae, which have very identifiable patterns of temporal variation in brightness and also happen to be excellent standard candles (i.e., they all have roughly the same intrinsic luminosity). These are two major reasons why these stars are used to study Galactic structure. To further our understanding of our own Milky Way galaxy and RR Lyrae stars, it is crucial to identify clean samples of them in large astronomical time-series photometric data sets. The photometric variations of RR Lyrae can be confused with the light curves of other types of photometrically variable astronomical objects such as distant quasars and active galactic nuclei (AGNs), so it is often necessary to visually vet the light curves. The identification of and discrimination between different kinds of variable objects can be assisted by computer algorithms that search for certain qualities present in the light curves of these variable objects. The broader goals of this research project are to better quantify the purity (degree of quasar/AGN contamination) and completeness of RR Lyrae in large time-domain surveys.
Tasks:
The SIP interns will:
- Run thousands of simulated quasar/AGN and RR Lyrae light curves through two stages of Yuting’s automated RR Lyrae search via empirical template fitting: (1) initial broad/coarse periodogram search and (2) subsequent Zoomed-in/fine periodogram search;
- Compute the statistics of simulated quasars/AGNs with high scores and simulated RR Lyrae with low scores (using some standard score threshold to define high vs. low scores); and
- Visually vet unfolded and folded light curves of a small, but representative subset of objects in each of the above two categories.
Required skills for interns prior to acceptance: None
URL: https://app.ubinum.com/lab/raja-uco-lick-observatory
AST-04: Exploring the Kinematics and Substructure of M31 and M32: A Comparative Analysis of SPLASH and DESI Surveys
Primary mentor: Rohit Raj (Juniata College, PA)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: In person/hybrid on the UCSC campus
Number of interns: 3 + CSIP
Project description:
The Andromeda galaxy (M31) and its satellite galaxy M32 are two of the closest and most studied galaxies in the sky. However, there is still much we don’t know about their formation and evolution. This research project offers a unique opportunity to compare two cutting-edge astronomical surveys: the SPLASH and DESI surveys of M31 and M32. By comparing the kinematics and substructure of these galaxies as measured by these two surveys, the mentor and SIP/TSIP interns will gain insights into the history of these two galaxies, their merger and accretion events, and the distribution of dark matter in their halos. This research project is ideal for SIP/TSIP interns who are interested in galaxy formation and evolution, spectroscopic techniques, and data analysis. The interns will work with real data and learn how to manipulate, analyze, and interpret large datasets, while contributing to our understanding of the Universe.
Tasks:
The SIP/TSIP interns on this research project will carry out the following data analysis tasks: (1) use existing source photometry and astrometry catalogs derived from PHAT/PHAST survey Hubble Space Telescope images asking with the ground based seeing FWHM to determine the fractional contribution of each star to each Keck/DEIMOS slit in the SPLASH survey and each DESI fiber; (2) compare the predicted (HST) vs. observed (SPLASH and DESI) spectral continuum strength; and (3) compare the SPLASH and DESI spectra.
Required skills for interns prior to acceptance: None
URL: https://app.ubinum.com/lab/raja-uco-lick-observatory
AST-05: Time-Series Spectroscopy of RR Lyrae Stars in the Milky Way
Primary mentor: Yuting Feng
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
RR Lyrae stars are important tracers in the study of the structure of our Milky Way galaxy because of two characteristics: (1) they have a characteristic pattern of periodic brightness variations; and (2) they are “standard candles”, meaning that they all have roughly the same time-averaged luminosity. Moreover, the stellar pulsations that RR Lyrae undergo provide insight into the interior structure of stars and the stellar evolutionary processes of stars that are located in the so-called “instability strip” in the Herzsprung-Russell diagram. This research project will explore spectra of relatively faint RR Lyrae in the Milky Way stellar halo to better understand: (a) how to use these stars as kinematical/dynamical tracers of the Milky Way’s dark matter halo; and (b) how to connect the kinematics of these RR Lyrae stars with their brightness variation, to better understand the physics of their stellar pulsations.
Tasks:
The SIP interns will:
(1) Explore mathematical methods like cross-correlation (Python based) to extract the velocities from the Keck/ESI spectra of faint RR Lyrae stars; and
(2) Use literature results to calibrate these velocities to the center of mass velocities, which could better represent the dynamical movement of RR Lyrae stars in response to the gravity of the (mostly) dark matter in the Milky Way halo.
Required skills for interns prior to acceptance: Computer programming, statistical data analysis
URL: https://app.ubinum.com/lab/raja-uco-lick-observatory
AST-06: Broad Emission-Lined Luminous Sources (BELLS)
Primary mentor: Olivia Gaunt (Tufts University, MA)
Secondary mentor: Preksha Sethia (University College London, UK)
UCSC faculty contact: Prof. Raja Guhathakurta
Location: 100% remote and online
Number of interns: 4 + TSIP
Project description:
The Triangulum Galaxy (M33) is the third largest member (by mass) of the Local Group. M33 is a dwarf spiral galaxy well-known for its active star-forming regions that are rich in the ionized gas phase of the interstellar medium (ISM). While inspecting spectra from the Triangulum Extended (TREX) survey, the mentor’s research group discovered six point-like broad emission lined luminous sources (BELLS) in and around the central star-forming region of M33. The SIP/TSIP interns will use Python spectroscopic data analysis techniques to detect and carry out an investigation into the nature of this mysterious set of rare emission lines in M33 and other rare/weak emission lines in both M31 and M33. The interns will also have the opportunity to work with brand new observational data taken in Nov. 2022!
Tasks:
The SIP/TSIP interns will develop their own Python code and use existing Python code to work with spectroscopic data from the DEIMOS spectrograph on the Keck II 10-meter telescope. This research project will initially involve processing of the 1D spectroscopic data to remove the effects of the Earth’s atmosphere (airglow) and instrumental signatures, subsequent analysis of the 2D spectra, and the creation and critical analysis/interpretation of a series of data diagnostic plots.
Required skills for interns prior to acceptance: None, computer programming and statistical data analysis recommended
URL: https://app.ubinum.com/lab/raja-uco-lick-observatory
AST-07: The Kinematics, Physical Conditions, and Chemical Abundances of Ionized Gas in the Andromeda Galaxy (M31) and a Comparison to the Triangulum Galaxy (M33)
Primary mentor: Aparajito Bhattacharya (St. Xavier’s College, Kolkata, India)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: 100% remote and online
Number of interns: 3
Project description:
The space between stars within galaxies is filled with interstellar medium (ISM), a cocktail of various gases and cosmic dust. In the vicinity of massive stars, and in star-forming regions, these gases get ionized and give off characteristic ISM spectral emission lines. The Andromeda galaxy (M31) and the Triangulum galaxy (M33) are spiral galaxies in the Local Group with active star forming regions. They provide an excellent opportunity to study the dynamical properties, physical conditions (e.g., density, temperature), and chemical composition of the ISM, through emission lines.
Tasks:
In this research project, the SIP interns will use data from the DEIMOS spectrograph of the Keck II 10-m telescope collected by the mentoring team as part of the Spectroscopic and Photometric Landscape of Andromeda’s Stellar Halo (SPLASH) survey and the Triangulum Extended (TREX) survey. The kinematics of the ionized gases due to rotational dynamics of the galactic disk, and any deviation from it, will be measured using the Doppler shift of ISM emission lines. The SIP interns will also study the chemical abundances of various components of ISM, and look for rare emission lines In the Keck spectra (RELIKS).
Required skills for interns prior to acceptance: None
URL: https://app.ubinum.com/lab/raja-uco-lick-observatory
AST-08: Canada-France-Hawaii Telescope Legacy Survey Deep Fields: Phase Distance Correlation (PDC) Periodograms of Variable Star Candidates
Primary mentor: Manjima Talukdar (St. Xavier’s College, Kolkata, India)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: 100% remote and online
Number of interns: 3
Project description:
Studies of the density profile, substructure, and kinematics of the Milky Way’s extended stellar halo provide an insight to our galaxy’s formation and accretion history. It has long been recognized that RR Lyrae, a type of periodic variable stars commonly found in globular clusters, are arguably the most reliable tracers of the Milky Way’s stellar halo. Their relatively high luminosity and periodic pattern of photometric variation distinguish them from other astronomical sources of comparable apparent brightness and color, and make them excellent standard candles. They can also be used to measure the chemical abundance of the halo. The Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) is a deep, multi epoch photometric survey of four 1 square degree fields in the five photometric bands (ugriz filters) with excellent depth and exquisite cadence. In this research project, SIP interns will use the deep fields component of CFHLS database to study the short-period variable stars.
Tasks:
The SIP interns will carry out the following tasks: (1) phase distance correlation (PDC) analyses of five-band time-series photometric data to search for different types of periodic variable stars in the CFHTLS deep field database; and (2) characterization of the pulsation and other properties of different types of variable stars found in the CFHTLS Deep Fields database.
Required skills for interns prior to acceptance: None
URL: https://app.ubinum.com/lab/raja-uco-lick-observatory
AST-09: Automating a Multiwavelength Analysis of the Blazar Mrk 421
Primary mentor: Dr. Olivier Hervet
UCSC faculty contact: Prof. David Williams
Location: In person/hybrid on the UCSC campus
Number of interns: 4
Project description:
Blazars are the brightest stationary sources in the Universe. Their powerful plasma jets powered by feeding supermassive black-holes emit radiation across the whole electromagnetic spectrum, from low radio frequencies to very-high-energy gamma rays. The general behavior of these sources is still puzzling to the scientific community, especially on how they seemingly erratically produce massive flares with complex counterparts. At UCSC, the mentor’s research group is tackling this issue by organizing a dense monitoring campaign of one of the brightest blazars, Mrk 421, over multiple years and with various telescopes. Having already gathered a large amount of data, the research group now needs to organize, analyze, and diffuse this dataset to the scientific community. The research group plans to develop an automatic pipeline at UCSC that will analyze new data every day and centralize the results onto a web platform.
Tasks:
The SIP interns will continue ongoing work started last year on implementing automatic analysis pipelines on our local computer cluster at UCSC. Each intern will be in charge of analyzing data from different observatories. There will be very high energy data from the VERITAS observatory in Arizona, gamma-ray data from the NASA space telescope Fermi-LAT, X-ray and UV data from the NASA space telescope Swift and additional optical data. The interns will also contribute to developing a web page that will display the combined results of these analyses to build lightcurves and broadband spectral energy distributions of Mrk 421. If time allows, the interns will participate in testing theoretical models on these data. By working on a local computer cluster and web implementation, the SIP interns will develop skills in Linux-bash commands, Python scripts, and HTML language. The interns will also get insights into statistical data analysis, astrophysical ideas, and the operation of multiple kinds of telescopes.
Required skills for interns prior to acceptance: Computer programming
URL: https://www.olivierhervet.com/
AST-10: Optimization of Data Cleaning for the Schwarzschild-Couder Telescope Camera
Primary mentor: Miguel Escobar Godoy
Secondary mentor: Dr. Olivier Hervet
UCSC faculty contact: Prof. David Williams
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
The Universe emits electromagnetic (EM) radiation of varying energy scales and it is necessary to observe it through all the different energy spectrum in order to understand it. The most energetic form of EM radiation are very-high-energy-gamma rays. Although Earth’s atmosphere is opaque to gamma-rays, these interact with nuclei in the atmosphere to produce a shower of particles that travel faster than the atmospheric speed of light and induce Cherenkov radiation which in turn can be detected by Imaging Atmospheric Cherenkov Telescopes (IACTs). At UCSC, the mentor’s research group is working on the commissioning of the ground based Cherenkov Telescope Array (CTA); the next generation of IACTs. A candidate telescope for CTA is the Schwarzschild-Couder Telescope (SCT) which is comprised of a finely pixelated camera which leads to excellent image resolution. This, in turn, means large volumes of data will be collected that need to be efficiently read out. It is of utmost importance to develop algorithms that will filter out useful events and discard other background events. The mentor’s research group’s task at UCSC is to develop and study algorithms that optimally implement cleaning and reduction methods on simulated data with the goal of eventually applying this to real data.
Tasks:
The SIP interns will continue ongoing work of testing out different cleaning and data reduction methods on our local computer cluster at UCSC. The intern will try out these methods on the most updated version of simulated CTA data. In addition, these methods allow for variation of many parameters that can be fine tuned in order to get the best result. The interns will study which parameters optimize these methods. The students will also study how the different cleaning and reduction methods as well as the variation of parameters inside these methods affect the Hillas parameters. The Hillas parameters are values associated to the image generated in the camera of an IACT that are used to extract information of the gamma-ray such as its direction and energy. If possible and time allows, the student will study the instrument response functions (IRFs) and how they vary based on the cleaning/reduction methods. IRFs gives you information on the performance of your telescope as a function of different parameters. All of these tasks involve the use of a Linux computer as well as ctapipe, a python based framework for low-level processing algorithms of CTA data. The interns will develop skills on Linux-bash commands, Python scripting as well as learn different aspects of astroparticle physics from how an IACT works to the scientific studies that can be performed through gamma-ray astrophysics.
Required skills for interns prior to acceptance: Computer programming
AST-11: Probing a Nearby Galaxy Group With a Fast Radio Burst
Primary mentor: Sunil Simha
UCSC faculty contact: Prof. J. Xavier Prochaska
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Fast radio bursts (FRBs) are millisecond-duration radio-transient sources that are gaining popularity as probes of ionized gas in recent years. Their short-duration pulse is modulated as it travels through plasma in the foreground Universe. For example, the pulse is dispersed, like sunlight traveling through a prism, and this results in a time delay in the arrival of the lower frequency components of the pulse compared to the higher frequencies. This can be measured accurately, informing us of the total column density of free electrons along the line of sight. In this research project, the SIP mentor and SIP interns will focus on one FRB sightline, which is known to intersect a nearby (<20 Mpc) galaxy group. The aim is to infer the nearby galaxy group’s contribution to the FRB dispersion from public photometry and distances to galaxies. The research team shall further infer the contribution of other foreground galaxies targeted using the Gemini/GMOS spectrograph. This research project will ultimately factor into the ongoing FLIMFLAM survey and further our understanding of the distribution of ionized gas in cosmological distance scales.
Tasks:
The SIP interns will work on the following tasks:
(1) Search existing public data archives for galaxy properties (masses and distances) of the members in the nearby group;
(2) Reduce the Gemini/GMOS spectra of galaxies targeted in the field (time permitting);
(3) Estimate the spectroscopic redshifts and thus infer distances to the GMOS galaxies; and
(4) Infer the fraction of the FRB dispersion arising from the galaxies studied above.
Required skills for interns prior to acceptance: Computer programming
AST-12: Time-Series Spectroscopy of RR Lyrae Stars in the Milky Way
Primary mentor: Joey Salinas
Secondary mentors: Roy Doyel, Yuting Feng
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
RR Lyrae stars are important tracers in the study of the structure of our Milky Way galaxy because of two characteristics: (1) they have a characteristic pattern of periodic brightness variations; and (2) they are “standard candles”, meaning that they all have roughly the same time-averaged luminosity. Moreover, the stellar pulsations that RR Lyrae undergo provide insight into the interior structure of stars and the stellar evolutionary processes of stars that are located in the so-called “instability strip” in the Herzsprung-Russell diagram. This research project will explore time-series spectra of relatively bright RR Lyrae in the Milky Way to better understand: (a) how to use these stars as kinematical/dynamical tracers of the Milky Way’s dark matter halo; and (b) the physics of stellar pulsations. Over the last few years, the mentor’s research team has obtained time-series spectra for about a dozen stars using the ESI spectrograph in echellette mode and the DEIMOS spectrograph with the 1200G and 600ZD gratings.
Tasks:
The SIP interns will carry out the following data analysis tasks on the RR Lyrae time-series spectroscopic data set:
(1) Measure the Doppler shift of individual Balmer absorption lines and metal absorption lines for each spectrum (multiple spectra for each star);
(2) Plot velocity as a function of pulsation phase for the different Balmer absorption lines and metal absorption lines for each star; and
(3) Compare the velocity curves with model predictions and other empirical data in order to develop a prescription for converting an instantaneous velocity measurement into the center-of-mass velocity.
Required skills for interns prior to acceptance: None
URL: https://app.ubinum.com/lab/raja-uco-lick-observatory
AST-13: The Kinematics of the Enigmatic Ultra Compact Dwarf Galaxy M32 and the Southern Disk of the Andromeda Galaxy (M31)
Primary mentor: Douglas Grion Filho
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: In person/hybrid on the UCSC campus
Number of interns: 5
Project description:
The Andromeda galaxy (M31) and the dwarf satellite galaxies that orbit it offer a (relatively speaking!) close-up view of galaxy formation and evolution. The ultra-compact dwarf (UCD) satellite M32 is a rare kind of galaxy and its nature and origin remain poorly understood. M32 is superposed against the southern portion of the disk of M31. In Fall 2022, the mentor’s research group obtained a large volume of spectra of M31 and M32’s resolved stellar population using the DEIMOS spectrograph on the Keck II 10-meter telescope in Hawaii. These spectra, along with spectra from other parts of M31’s disk obtained over the last decade or more, will be useful for placing observational constraints on the past, ongoing, and future tidal interaction between M31 and M32.
Tasks:
The SIP interns will: (1) learn to vet the Fall 2022 Keck DEIMOS multi object spectra of M31 and M32’s resolved stellar population and classify radial velocity measurements as secure, marginal, or unreliable; (2) analyze the stellar kinematics of M32 and M31’s southern disk and compare the latter to HI kinematics; and (3) compare and contrast the stellar kinematics (i.e., asymmetric drift, velocity dispersion) of the southern and northern portions of M31’s disk.
Required skills for interns prior to acceptance: None
Biomolecular Engineering
BME-01: Comparative Genomics of Encephalitozoon Hellem Strains
Primary mentor: Anne Caroline Mascarenhas Dos Santos (Illinois Institute of Technology, IL)
Faculty contact: Prof. Jean-Francois Pombert (Illinois Institute of Technology, IL)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: 100% remote and online
Number of interns: 3
Project description:
Microsporidia are a group of understudied fungi-related obligate intracellular parasites and the human-infecting species (e.g., Encephalitozoon spp.) are classifed as category B priority pathogens by the CDC. The Encephalitozoon species is known to have the smallest known eukaryotic genomes, which makes them excellent candidates to study parasitism from a genomic perspective. In this research project, the mentor’s research group has sequenced the Encephalitozoon hellem 50451 genome with long- and short-read sequencing technologies. The research group aims to assemble and annotate the genome using freely available tools, and perform comparative genomics analysis between different E. hellem strains, which could help in the development of future outbreak traceability approaches.
Tasks:
The SIP interns will be responsible for carrying out all of the data analysis. The interns will filter sequencing data, assemble them, verify fragmentation of assembly, and assess genetic distances through read mapping and variant calling. The interns will need to learn Linux/bash command line operations in order to navigate the remote servers.
Required skills for interns prior to acceptance: None
URL: https://www.pombertlab.org
BME-02: Molecular Docking and Molecular Dynamics Study of TcmN Ligands
Primary mentor: Veronica Silva Valadares (Federal University of Minas Gerais, Belo Horizonte, Brazil)
Faculty contacts: Prof. Adolfo Henrique de Moraes (Federal University of Minas Gerais, Belo Horizonte, Brazil), Prof. Haribabu Arthanari (Harvard Medical School, MA)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: 100% remote and online
Number of interns: 3
Project description:
The N-terminal Tetracenomycin aromatase/cyclase (TcmN), an enzyme derived from Streptomyces glaucescens, is involved in polyketide cyclization and aromatization. Polyketides are diverse class metabolites with various pharmaceutical applications. Because TcmN is a promising enzyme for in vitro production of polyketides, it is important to understand the principles underlying TcmN interaction with its ligands and identify conditions that optimize TcmN function. In this research project, the mentor’s research group has identified point mutations that might enhance the protein’s thermal stability. The research group will use molecular docking and molecular dynamics studies to compare mutants’ interaction with TcmN ligands.
Tasks:
The SIP interns will be responsible for carrying out all of the data analysis. The interns will review the structure of both protein and its ligands, prepare the simulation system, run the simulations, and analyze the results. The interns will need to learn Linux command line operations to navigate the remote servers.
Required skills for interns prior to acceptance: None
BME-03: Computational Biology to Study Neuroblastoma, a Pediatric Cancer
Primary mentor: Dr. Gepoliano Chaves
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: 100% remote and online
Number of interns: 7
Project description:
Neuroblastoma, a pediatric cancer of the neural crest tissue, accounts for 7% of malignancies diagnosed in children, but 15% of all pediatric oncology deaths. Therefore, understanding the biological mechanisms that drive aggressive neuroblastoma may help develop therapy to improve outcome in patients. As tumors grow, there is increased necessity of blood and nutrient supply, provided through the formation of blood vessels in a process called angiogenesis, which aimes to nourish cancer cells. However, tumor growth is so much faster than normal cell growth that cancer cells exceed oxygen supply levels, creating a hypoxic condition at the tumor microenvironment. Hypoxia is a biological factor thought to contribute to aggressiveness. The mentor’s lab has identified important molecular players for the transduction of the hypoxia signal from the tumor microenvironment to the interior of the cells, particularly the cellular nucleus, where gene expression control is maintained. The mentor’s lab has contributed to the identification of ten-eleven-translocation (TET) enzymes and the product of their activity, 5-hydroxymethyl-cytosine (5-hmC), as factors mediating tumor modifications in response to the hypoxia stimuli. In this research project, the SIP mentor and interns will investigate patterns of gene expression in neuroblastoma tumors and cells, using publicly-available data and data from the mentor’s lab to characterize the biology driving neuroblastoma aggressiveness.
Tasks:
The SIP interns will:
• Download publicly available neuroblastoma datasets;
• Interact with R and other computer programs to extract biological information;
• Determine what relevant information to show to the SIP community audience and professional scientific audience;
• Present research data; and
• Write scientific papers for junior science journals.
Required skills for interns prior to acceptance: None
Chemistry and Biochemistry
CHE-01: Electrochemistry and Energy Storage
Primary mentor: Ella Davidi
UCSC faculty contact: Prof. Yat Li
Location: In person/hybrid on the UCSC campus
Number of interns: 4
Project description:
Advanced Supercapacitors for energy storage: Electric charge can be stored in a double-layer capacitor. Double-layer capacitance appears at the interface between a conductive electrode and an adjacent liquid electrolyte. At the boundary of these two layers, charge with opposing polarity forms, one at the surface of the electrode, and one in the electrolyte. These two layers, electrons on the electrode and ions in the electrolyte, are typically separated by a single layer of solvent molecules that adhere to the surface of the electrode and act like a dielectric in a conventional capacitor. In this research project, the SIP mentor and interns will use 3D printing techniques to print carbon based Supercapacitors, and will demonstrate double layer characterization using electrochemical measurement.
Tasks:
In this research project, the SIP interns will work on reading academic literature and performing the following experiments in the lab:
- Making electrolyte solutions;
- Setting up electrochemical cells;
- Preforming electrochemical measurements; and
- Analyzing results of experiments.
Required skills for interns prior to acceptance: None
URL: https://li.chemistry.ucsc.edu/
CHE-02: Ruthenium-Based Electrocatalysts for Hydrogen Evolution Reaction
Primary mentor: Bingzhe Yu
UCSC faculty contact: Prof. Shaowei Chen
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Hydrogen (H2) has been considered as a potential candidate to substitute fossil fuels in the future due to its renewability and cleanliness. Currently, although Platinum (Pt)-based nanomaterials are deemed to be the best electrocatalysts for hydrogen evolution reaction (HER) in acidic electrolytes, their limited availability and high cost significantly impede their large-scale applications in energy relevant conversion devices. Recently, ruthenium (Ru) has attracted widespread attention due to its remarkable activity in alkaline HER and lower price compared to Pt. Deeper research is necessary in order to make progress in this field of research. The mentor will teach the synthesis of nanomaterials and the basic experimental methods of electrochemistry.
Tasks:
The SIP interns will:
- Learn and practice lab safety;
- Conduct simple experimental operations;
- Learn how to synthesize nanomaterials; and
- Learn how to use an electrochemical station.
Required skills for interns prior to acceptance: None
URL: https://chen.chemistry.ucsc.edu/
CHE-03: Nanocatalysts for Electrochemistry
Primary mentor: Dingjie Pan
UCSC faculty contact: Prof. Shaowei Chen
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
The recent hydrogen production in industry still depends on natural gas. Water constitutes 71 percent of the earth but the high energy barrier fir water splitting has limited the extent of its application. The SIP interns will spend this summer to learn how to design, synthesize, and analyze new electrocatalysts for water splitting.
Tasks:
The SIP interns will conduct electrochemistry experiments, prepare samples for characterization, and carry out data analysis.
Required skills for interns prior to acceptance: None
URL: https://chen.chemistry.ucsc.edu/
CHE-04: Isolation of Natural Products
Primary mentors: Leah Bouthillette, Rebecca Pelofsky
UCSC faculty contact: Prof. John MacMillan
Location: In person/hybrid on the UCSC campus
Number of interns: 4
Project description:
Natural products or secondary metabolites are evolved to serve a biological role in nature and therefore are structurally diverse and complex. These molecules have been harnessed for medicinal purposes in addition to inspiring chemists to produce new kinds of reactions and molecules. Our lab has a large collection of marine bacteria in addition to a fraction library which has been used for projects involving anti-cancer and mosquitocidal drug activity, novel kinds of labeling for non-enzymatic chemistry discovery, and the discovery of novel biosynthetic mechanisms. Isolation and analytical methods will be used in this project to study these molecules further and learn more about their structure and how they are made.
Tasks:
The SIP interns will learn how to use instrumentation for purifying organic compounds: high performance liquid chromatography (HPLC); nuclear magnetic resonance (NMR) spectroscopy; liquid-chromatography mass spectrometry (LC/MS); fermentation and culturing of marine microbes; and gene cluster identification and knock outs.
Required skills for interns prior to acceptance: None
URL: https://macmillanlab.sites.ucsc.edu/
CHE-05: Designing High-Energy-Density Rechargeable Zinc Batteries
Primary mentor: Xinzhe Xue
UCSC faculty contact: Prof. Yat Li
Location: 100% remote and online
Number of interns: 3
Project description:
Aqueous zinc batteries (AZBs) are considered to be one of the most attractive candidates for the new generation of energy storage, due to their high capacity and safety. To date, different kinds of cathode materials, electrolytes, and structurally engineered electrodes have been exploited to achieve higher energy density. It is critical to review the state-of-the-art AZB systems, identify the fundamental questions that limit the device’s performance, and design materials to tackle these scientific and technological challenges.
Tasks:
The SIP interns will: (1) read the scientific literature to review the challenges and opportunities of aqueous zinc batteries, and understand the mechanisms and design principles of high energy density AZBs; (2) design an electrode or electrolyte system for high energy density AZBs; (2) design experiments to fabricate and test the materials; and (4) analyze the electrochemical behaviors obtained from the electrochemical tests.
Required skills for interns prior to acceptance: None
URL: https://li.chemistry.ucsc.edu/
CHE-06: Optimizing Hematite for Electrochemical Devices
Primary mentor: Samuel Eisenberg
UCSC faculty contact: Prof. Yat Li
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Iron (III) oxide (hematite) is a semiconductor material with promising energy generation and storage applications due to its low cost, non-toxicity, and stability. By manipulating its nanostructure and composition, many important physical properties can be tuned. Improving the material’s light-absorbing ability, conductivity, and capacitance will allow hematite to be introduced in industrially feasible clean electrochemical devices.
Tasks:
The SIP interns will assist in preparing reagents and solutions, synthesizing semi-conductor materials, analyzing samples using various spectroscopic, microscopic and electrochemical techniques, and processing the resultant data to draw conclusions on our experiments.
Required skills for interns prior to acceptance: None
URL: https://li.chemistry.ucsc.edu/people
CHE-07: Structural-Engineered Catalytic Materials for High-Rate Alkaline Water Splitting
Primary mentor: Qiu Ren
UCSC faculty contact: Prof. Yat Li
Location: 100% remote and online
Number of interns: 3
Project description:
Alkaline water splitting (AWS) is a promising technology for green hydrogen production. To generate hydrogen at industrial scale, AWS needs to be operated at a high current density. However, the formation of large amounts of gas bubbles (hydrogen and oxygen gases) on catalytic electrodes limits the maximum current density and thus productivity of AWS. In this project, we aim to tackle this challenge by building architected electrodes to facilitate bubble generation, detachment and releasing during high-rate AWS. This research project involves the design and fabrication of novel catalytic materials, electrochemical measurements and data analysis. The SIP interns will learn the basic knowledge of electrochemistry and catalysis, and design new catalytic electrodes.
Tasks:
The SIP interns will:
(1) Read the literature to understand the challenges and opportunity of AWS for green hydrogen production, the importance of mitigating bubble issues, and the basic knowledge of electrocatalysis;
(2) Design a catalytic electrode for facilitating bubble generation, detachment, and releasing bubbles in high-rate AWS;
(3) Design experiments to fabricate and test the designed electrodes; and
(4) Analyze the structural characterization and electrochemical data obtained from experiments.
Required skills for interns prior to acceptance: None
Computational Media
CPM-01: Educational Technologies and Research Ideation
Primary mentor: Dustin Palea
UCSC faculty contact: Prof. David Lee
Location: 100% remote and online
Number of interns: 3
Project description:
Over the summer we’ll be working on two projects. The first project asks: How might we design systems that scale experiential learning? To investigate this question, we’re working on building a crowd annotation platform called Annota. This web application introduces learners to the qualitative coding process by allowing them to make annotations on interview transcripts. Importantly, they are not only practicing their annotation skills but (we believe) that they are also producing valuable data that can then be used to help other learners i.e. learnersourcing. Rather than teaching through traditional methods which can be costly and thus limited (e.g. apprenticeship learning), our hope is to provide more opportunities to learners who can instead rely on technology and their peers. The second project, related to the first, is interested in developing generalizable ways that computational systems and crowds of people can work together to produce educational resources that help provide mentorship at scale. This project is still in its very early stages, meaning that it’s a great opportunity to learn how researchers generate and evaluate ideas (important for those interested in potentially going to grad school and/or contributing to scientific research).
Tasks:
There is a wide range of tasks for the SIP interns to engage in, including the following: (1) web development: HTML, CSS, Javascript, Angular web framework, and Google Firebase; (2) UX design and research: UI design in Figma, designing and conducting user surveys and interviews, analyzing qualitative data; and (3) research: scoping out a research idea – articulation of ideas, reviewing related work, etc. Prior experience is certainly a bonus, but isn’t required as the mentor will be teaching the interns all the skills they need.
Required skills for interns prior to acceptance: None
URL: https://tech4good.soe.ucsc.edu/#/
CPM-02: Public Interest Technology
Primary mentor: Amelia Wang
UCSC faculty contact: Prof. David Lee
Location: 100% remote and online
Number of interns: 3
Project description:
As higher education today lacks experiential learning and community engagement, the mentor’s aim is to design/help support computational ecosystems for community-engaged learning. This research project focuses on the development, design, and evaluation of a platform to help support alignment in student/community collaborations.
Tasks:
The SIP interns will be expected to develop skills in interviewing and analysis to help evaluate the mentor’s platform with possible additions of project design, UI/UX design, and/or platform/code development.
Required skills for interns prior to acceptance: None
URL: https://tech4good.soe.ucsc.edu/#/
CPM-03: Game-Making Tools Survey
Primary mentor: Jared Pettitt
UCSC faculty contact: Prof. Nathan Altice
Location: 100% remote and online
Number of interns: 3
Project description:
There are many different tools used to produce different kinds of video games, from casual tools like Twine, to professional tools like Unity 3D. These tools have, built into their design, certain affordances or expectations that shape what people tend to make using them. The mentor is working on research regarding game-making software, and this research project is a survey of different game-making tools, by using the tools to produce small games and then evaluating them afterwards. If the SIP interns are interested in making games, either in learning how to use high-level software, or just want to learn how to do it because it seems fun (it is), then they will definitely find this research project interesting to work on!
Tasks:
The SIP mentor and interns will be using several design game creation tools to make small games over the course of the summer, while evaluating how using the tool feels and how its design affects what they make using it. There are many tools that do not require any kind of programming or video game knowledge at all, so if the interns are at all interested but feel that they may not know enough to be helpful, they should not worry about that! The SIP interns will be learning, making games with, and evaluating several of the following tools, depending on their programming skill level: Twine, Bitsy, Pico-8, Unity 3D, Unreal Engine, and GameMaker.
Required skills for interns prior to acceptance: Computer programming
CPM-04: Designing Technologies for Facilitating Youth Career Exploration and Identity Formation
Primary mentor: Hayat Malik
UCSC faculty contact: Prof. David Lee
Location: 100% remote and online
Number of interns: 4
Project description: Starting career assessment and exploration early is critical for youth and students. To support youth in their career journey, we employ multiple methods that leverage social media and online platforms to assist youth in self reflection of their aspirations and seek out in-depth information about potential career options. We design technologies that aim to bridge the disconnect between youth with their parents and mentors and encourage them to develop their vocational identity.
Tasks:
The SIP interns can partake in a variety of the following tasks:
(1) Research work — scoping out prior research work, analyzing qualitative or quantitative data, designing user studies (surveys/interviews), and designing usability/evaluation studies of certain platforms;
(2) UI design —designing user interfaces on Figma, and sketching/brainstorming possible design decisions for platforms; and
(3) Web development — developing user interfaces (HTML/CSS), and developing a platform (Angular/Firebase).
Required skills for interns prior to acceptance: None
URL: https://tech4good.soe.ucsc.edu/
CPM-05: Embodied Game Design
Primary mentor: Samuel Shields
UCSC faculty contact: Prof. Edward Melcer
Location: 100% remote and online
Number of interns: 4
Project description:
Video games have a unique ability to create a feeling of embodiment in players. That sense of embodiment, in turn, can be used to help people. The ALT Games lab focuses on using games and their unique emergent properties to create positive outcomes in user’s lives. Interns in this group will have the option of contributing on any of the following projects:
(1) A game to teach trauma-informed yoga as a PTSD intervention;
(2) A generative AI system that produces video games based on player sentiment; and
(3) A study that investigates player perception of balance.
The SIP interns will be exposed to a basic style of project management and will have the option to contribute where their talents are — work is available in art, design, research, and coding. Background in any of the aforementioned areas will give the interns the most value from contributing, as will a love for games!
Tasks:
The SIP interns can contribute in one or more of the following ways:
(1) Creating visual effects and assets for ongoing projects;
(2) Creating audio effects and assets for ongoing projects;
(3) Improving, Replacing, or Adding new AI features in ongoing projects;
(4) Performing UI/UX design and User Testing; and
(5) Creating new data analysis strategies.
Required skills for interns prior to acceptance: None
URL: https://altgameslab.soe.ucsc.edu/
CPM-06: Conversational Interface Design for Large-Scale
Primary mentor: Kehua Lei
UCSC faculty contact: Prof. David Lee
Location: 100% remote and online
Number of interns: 3
Project description:
The goal of this research project is to explore novel conversational user experience (UX) design for communication with a large group of people. The mentor’s research group now has two research directions. The first is building a survey platform that blends qualitative and quantitative data collection. It also allows users to collaborate and build on others’ responses. The second one is building a platform for expressing and building gratitude in online communities.
Tasks:
The SIP interns will carry out some or all of the following tasks: (1) designing user interfaces for one of the platforms; (2) learning how to develop platforms; (3) running tests of the platform; and (4) conducting an evaluation on the platform through surveys and/or interviews.
Required skills for interns prior to acceptance: None
URL: https://tech4good.soe.ucsc.edu/
CPM-07: Social Emotional Tech With a Focus on Maker Hardware
Primary mentor: James Fey
UCSC faculty contacts: Prof. Katherine Isbister, Prof. Raquel Robinson
Location: 100% remote and online
Number of interns: 4
Project description:
As part of an on going series of research through design activities into technology with a social emotional focus, the mentors propose a research project in which the SIP interns will create a series prototype designs aimed to create a way of communicating emotional state to others nonverbally through different methods of input and output. The mentors will guide this design process but the interns will have a high degree of freedom when it comes to execution.
Tasks:
The SIP interns will:
—Conduct background research into the existing state of the art of notifications and nonverbal and non-textual communication;
—Engage in practical design research activities;
—Create working prototypes using commonly available maker hardware or mobile devices; and
—Use project management tools such as Asana and Slack/Discord to keep all team members apprised of project tasks and projects.
Required skills for interns prior to acceptance: None
URL: https://setlab.soe.ucsc.edu/about/
CPM-08: Acculturative Game Design with Latine Community
Primary mentor: Samantha Conde
UCSC faculty contact: Prof. Sri Kurniawan
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
The mentor offers an exciting project that will enable interns to gain valuable experience in developing an application/game that aims to reduce acculturative stress among first-generation Latine-Americans. The primary objective of the application is to facilitate communication and bridge the gap between different generations and values surrounding identity and sexuality. The interns will have the unique opportunity to design and develop an application/game based on the findings from a focus group conducted by the mentor that covers critical topics such as acculturative stress, intergenerational relationships, communication strategies, and games.
Tasks:
There are a variety of opportunities for the SIP interns to work on this research project based on their interests and expertise. These opportunities include: (1) collaborating with the mentor and other interns to design game mechanics and create storyboards that align with research findings; (2) utilizing game development software (Unity with Windows Laptop) to design and create application/game prototypes; (3) utilizing graphics design software to create assets for the application; and (4) utilizing UI Design tool (Figma) to design the layout of the application. In addition, if time permits, the interns may also have the chance to participate in the early stages of conducting usability testing to evaluate the effectiveness of the application/game.
Required skills for interns prior to acceptance: None, computer programming experience is recommended
URL: https://assist.soe.ucsc.edu/people
CPM-09: Generating Interesting Scenarios in the CARLA Simulator for Testing Autonomous Vehicles.
Primary mentor: Ishaan Anil Paranjape
UCSC faculty contact: Prof. Kate Ringland
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Ensuring safety of autonomous vehicles in simulation before deploying in the real world requires testing on a large number of scenarios. Identifying interesting scenarios is crucial since the range of possible scenarios is very large. We will be using a major open sourced simulator — CARLA and programming in python to find and generate interesting scenarios automatically. Characterizing scenarios as interesting or not is an open research question which will be explored during the internship! This will be done by interns reading research papers and going over different kinds of data related to scenario based testing of autonomous vehicles.
Tasks:
The SIP interns will: (1) explore the CARLA simulator and its features; (2) program the movement of some cars and pedestrians in the simulator; (3) parse data and extract interesting scenarios; (4) run these scenarios in CARLA; and (5) evaluate a vehicle’s response to these scenarios. The following laptop specifications are needed: Ubuntu or Windows, 200 GB or more disk space, and a separate GPU with 8 GB or more memory.
Required skills for interns prior to acceptance: Computer programming
CPM-10: Agent-Based Modeling Systems Survey
Primary mentor: Kyle Gonzalez
UCSC faculty contact: Prof. Michael Mateas, Prof. Noah Wardrip-Fruin
Location: 100% remote and online
Number of interns: 3
Project description:
Agent-based modeling is a form of computer simulation where the user designs and observes artificial agents interacting with each other in a shared environment. It is the basis for computer games like Dwarf Fortress or The Sims, where playful stories emerge organically from the simulation. It is also used widely across the social, life, and human sciences in order to create accurate models of the world and develop better theories. The mentor is researching how different approaches to agent-based modeling structure what we feel and know, and using this to develop critical and experimental games that support new kinds of experiences.
Tasks:
Over the course of the summer, the SIP interns will be working with several agent-based modeling systems and games and evaluating the process and experience of using them. The interns will also design and program their own creative visual computer simulations in p5.js with the guidance of the mentor.
Required skills for interns prior to acceptance: Computer programming
CPM-11: Surveys and Digital Ethnography of ADHD Content on Social Media
Primary mentor: Tessa Eagle
UCSC faculty contact: Dr. Kate Ringland
Location: 100% remote and online
Number of interns: 3
Project description:
Despite a common misconception that Attention-Deficit Hyperactivity Disorder (ADHD) is a childhood disorder, symptoms often persist into adulthood and many adults remain undiagnosed for a variety of reasons. Increased adoption of social media such as Instagram, TikTok, and Twitter has led to increased representation of neurodivergent community members with ADHD. As a result of the COVID-19 pandemic and increased social media use, many have come to recognize themselves in content made by social media members with ADHD and thus sought diagnoses of their own. Social media provides a valuable source of information, first-hand experiences, support, and validation through shared experiences. This project will look at data collected from social media platforms and surveys to see how identity presentation and content choices differ across apps. There is also the potential to look into ADHD-related ads for online services promising diagnosis and treatments and to survey users of these services to determine the benefits and potential problems.
Tasks:
The SIP interns will work on survey development, data collection, data analysis, data visualization, and qualitative research methods.
Required skills for interns prior to acceptance: None
URL: https://www.misfit-lab.com/
CPM-12: Scenario Generation for Autonomous Vehicles
Primary mentor: Abdul Jawad
UCSC faculty contact: Prof. Jim Whitehead
Location: In person/hybrid on the UCSC campus
Number of interns: 4
Project description:
Scenario-based testing of autonomous vehicles (AVs) in virtual environments has become an essential component of vehicle safety validation efforts because it is scalable, cost-effective, and safe. Critical and challenging scenarios for AVs are the key part of scenario-based testing. The recent trend for generating these critical and challenging scenarios is using game engine-based simulation tools such as CARLA (an Unreal game-engine-based simulator) and Apollo (a Unity game-engine-based simulator). This research project will explore techniques for generating critical and challenging scenarios in the open-source simulation tool CARLA. Specifically, critical scenarios that arise due to human limitations (cognitive, perceptive, motor, etc.) will be the core interest of the research project. The SIP interns will get involved in programming in Python. The interns will explore existing literature in related fields: AV testing, driver behavior modeling, and scenario generation.
Tasks:
In this research project, the SIP interns will conduct the following tasks:
(1) Short literature review to get familiar with the research;
(2) Learn to write programs in Python;
(3) Learn how to use the Unreal game engine; and
(4) Write a short paper at the end of the project.
Required skills for interns prior to acceptance: Computer programming, statistical data analysis
CPM-13: Virtual Reality (VR) Games for Sensory Rehabilitation
Primary mentor: Rohan Jhangiani
UCSC faculty contact: Prof. Sri Kurniawan
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
This research project focuses on building virtual reality (VR) games for people with conditions that might affect their senses. The game is a continuation of the mentor’s research group’s previous work that used VR to help aid in the treatment of amblyopia. This research project relies on existing research around vision rehabilitation, smell rehabilitation, and serious games. The interns will also use the Unity game engine to develop novel immersive games to aid in sensory rehabilitation.
Tasks:
The SIP interns can expect to gain knowledge in virtual reality, serious games, and assistive technologies through conducting literature reviews early in the program. The interns will also learn about the VR game development process in the Unity Game Engine.
Required skills for interns prior to acceptance: None
CPM-14: Game-Like Tutorials for Art Software
Primary mentor: Andrew Dunne
UCSC faculty contact: Prof. Eddie Melcer
Location: In person/hybrid on the UCSC campus
Number of interns: 3 + TSIP
Project description:
To teach their players how to play, video games employ interactive tutorials built into the games themselves. There is a large amount of design work around creating game tutorials that both teach and entertain players. Meanwhile, art software such as Photoshop or Blender often require users to learn the programs through external means such as Youtube tutorials. Would built-in gamelike tutorials for art software be more effective than current second-hand teaching methods? This research project aims to build a game-like tutorial for art software, and to see how effective game-like tutorials are for teaching everything from simple actions (e.g., ‘how to change the color of the paintbrush’) to abstract concepts (e.g., ‘how does using different brush textures affect how people perceive art?’). Hopefully, this research project will lead to better and more fun software tutorials!
Tasks:
The SIP/TSIP interns will:
—Study examples of video game and art software tutorials;
—Find and read research papers about tutorials, educational games, and other related topics;
—Discuss progress and ideas with others on the project;
—Design (brainstorm, plan, test, document) and build (program, make UI and other visual/audio assets) an interactive tutorial for some piece of art software; and
—Practice presenting findings in unique ways.
Required skills for interns prior to acceptance: None
CPM-15: A Review of Engagement with Failure in Behavior Change Apps
Primary mentor: Rebecca Lietz
UCSC faculty contact: Prof. Steve Whittaker
Location: In person/hybrid on the UCSC campus
Number of interns: 3 + TSIP
Project description:
Changing behaviors is a difficult process for individuals. It is even more difficult to deal with failed attempts at change, often repeatedly. Many fitness trackers, habit-building apps, and other behavior change technology are supposed to help users enact lasting changes in their lives. But how do they engage with users when they fail? This research project investigates how popular behavior change apps address failure and how those approaches compare to people’s actual lived experiences when they fail. To achieve this, the SIP/TSIP interns will review various features of existing behavior change apps, analyze their general approaches to failure, and assess how well they reflect people’s lived experience.
Tasks:
The SIP/TSIP interns will gain experience with data collection and analysis. The interns’ tasks will include: (1) reading relevant literature; (2) researching and reviewing popular behavior change technologies (e.g., fitness and diet trackers, habit-building apps) and how they address failure; and (3) analyzing and contextualizing the collected data.
Required skills for interns prior to acceptance: None
CPM-16: AI Anatomy Visualization
Primary mentor: Henry Zhou
UCSC faculty contacts: Prof. Michael Mateas, Prof. Noah Wardrip-Fruin
Location: 100% remote and online
Number of interns: 3
Project description:
Artificial intelligence (AI) with machine learning has been a hot topic of discussion in recent months, with the rise of text-to-image generation and ChatGPT. However, what is often ignored behind this excitement are the real humans and social consequences behind the acceleration of technology development. This research project aims to enable interns to create visualizations of how AI models are made, similar to the artwork “Anatomy of an AI System”, or other artworks that could bring forth issues regarding social justice in AI.
Tasks:
The SIP interns will learn to research articles on recent AI models and understand their production processes. The interns will also learn to program in p5.js and create visualizations. The interns’ final research projects will be simple web visualizations of the production processes of an AI model of their choice. This research project aims to familiarize interns with societal issues about AI and to develop basic programming skills for creating web visuals.
Required skills for interns prior to acceptance: None
CPM-17: Exploring Neurodivergent-Led Media Practices to Reframe Design Principles for Neurodiverse Multimodal Learning
Primary mentor: Yihe Wang
UCSC faculty contact: Prof. Kate Ringland
Location: 100% remote and online
Number of interns: 4
Project description:
This research project aims to explore the online video tutorial (e.g., YouTube videos) viewing habits of neurodivergent (ND) individuals (e.g., ASD, ADHD, and ASP) to redefine design principles for tailored multimedia learning experiences. ND people may have different preferred learning styles than neurotypical people. For instance, studies have indicated that captions can enhance audio-visual material retention for individuals with ADHD. However, the knowledge construction view of multimedia learning, coupled with the dual channel assumption, predicts that learning will decrease with captions due to the need to process redundant information (i.e., the redundancy principle). By studying neurodivergent individuals’ video tutorial learning habits, we can gain insights into their cognitive processing of multimedia learning materials and use these findings to reframe design principles that promote inclusive and effective multimodal learning experiences.
Tasks:
In this research project, the SIP interns will conduct the following tasks: (1) identify and analyze existing media practices initiated by neurodivergent individuals; (2) develop a set of design guidelines and recommendations; (3) create prototype multimodal learning materials that integrate the identified design principles; and (4) conduct pilot testing with neurodivergent individuals for feedback and validation.
Required skills for interns prior to acceptance: None
URL: https://www.misfit-lab.com/
CPM-18: Exploring Novel Contexts for the Wave Function Collapse Algorithm
Primary mentor: Bahar Bateni
UCSC faculty contact: Prof. Jim Whitehead
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
The Wave Function Collapse (WFC) algorithm is a tile-based method for generating content by following rules derived from the given examples. By incorporating statistical heuristics, the algorithm can enhance the results obtained from constraint solving. In this project, the interns will focus on utilizing novel heuristics for WFC and evaluating the impact of these heuristics on the quality of outcomes. The evaluation process will be done on various data types, including 2D data such as images and 3D data such as Minecraft structures.
Tasks:
The SIP interns’ tasks will include: (1) Python programming; (2) data collection; (3) visualization of data; (4) analyzing statistical properties; and (5) using statistical evaluation methods.
Required skills for interns prior to acceptance: None
CPM-19: Social Superpower Tools to Support VR Meetings
Primary mentor: Anya Osborne
UCSC faculty contact: Prof. Katherine Isbister
Location: 100% remote and online
Number of interns: 2 + CSIP
Project description:
This research project explores building social virtual reality (VR) technology to improve networked meetings in VR. The mentor’s research team has developed five experimental tools that they have identified as promising for supporting productive collaboration and social connection among remote and hybrid teams. These “Social Superpower Tools” include richly embodied and specialized techniques for balancing conversation, signaling emotion, crafting environments, shaping self-presentation, and managing time in VR meetings. The mentor will introduce these tools, including core human-computer interaction (HCI) methodologies that the mentor’s group has used to test the tools in the field with real teams. The SIP interns will try out these tools firsthand, using VR headsets, and apply this knowledge to generate ideas for social media posts based on their experience of using these tools.
Tasks:
The SIP interns should have access to VR Headsets (e.g., Meta Quest 1 or 2) and will conduct the following tasks: (1) literature review to get familiar with social VR research; (2) explore meeting sites in the existing consumer-facing social VR apps of their choice, individually or as a group; (3) try out the mentor’s group’s custom-built social VR environments in Mozilla Hubs; and (4) create a series of posts to be published on social media about their experience of using social superpower tools in VR (YouTube, Twitter, etc.)
Required skills for interns prior to acceptance: None
Computer Science/Computer Engineering
CSE-01: Internet Protocol Design; Development of a Shortest-Path Loop-Free Routing Protocol (Design and Simulation)
Primary mentor: Carl Ramfelt
Secondary mentor: Firouz Vafadari
UCSC faculty contact: Prof. J. J. Garcia-Luna-Aceves
Location: 100% remote and online
Number of interns: 3
Project description:
Today’s Internet applications demand a fast and reliable connection with less delay and real-time connection than ever before. Nevertheless, the currently used protocols cannot satisfy these needs. The problem is rooted in these protocols’ mechanisms, which make them useless for real-time applications. Most of them suffer from an integral part of graph theory, the Routing Loops, and facing a cyclic path while trying to detect the shortest route to the destination or, worse than that, blocking of a path will lead to no convergence. Our approach is to re-correct the mechanism of currently used protocols with innovative solutions and introduce a Loop-less shortest-path routing protocol with fast convergence and minimum path blocking. The interns will learn the basics of computer networks. The mentor will provide them with the network protocol categories and famous shortest-path algorithms. The interns will then diagnose the issues of well-known protocols and understand how our research addresses them. Eventually, the interns will implement and simulate the network protocols using NS3 and NetAnim while they learn how the protocol works.
Tasks:
In this research project, the SIP interns will follow a unique path of research and study to understand how to design network protocols that are the bases of the internet. Initially, the interns will learn the basics of computer networks (similar to CCNA). They will learn the network layers, IP, transport layer protocols, and SSH connection to a remote Linux server. Afterwards, the interns will learn about the newly designed protocols by the CCRG lab at UCSC that will replace the currently used ones and change how people communicate worldwide. The interns will use NS3 (Network Simulator V3) to implement simple network topologies and then move to the simulation of the CCRG’s newly designed protocols. Furthermore, the interns will learn the problems of currently used protocols while following the intriguing part of addressing them to develop a high-speed shortest-path loop-free one.
Required skills for interns prior to acceptance: Computer programming
CSE-02: Human-like Text Generation with Long Short-Term Memory Recurrent Neural Networks
Primary mentor: Saeed Kargar
UCSC faculty contact: Prof. Faisal Nawab
Location: 100% remote and online
Number of interns: 4
Project description:
The potential of artificial intelligence to emulate human thought processes goes beyond passive tasks such as object recognition and mostly reactive tasks such as driving a car. A large part of artistic creation consists of simple pattern recognition and technical skill. Our perceptual modalities, our language, and our artwork all have statistical structure. Learning this structure is what deep-learning algorithms excel at. Machine-learning models can learn the statistical latent space of images, music, and stories, and they can then sample from this space, creating new artworks with characteristics like those the model has seen in its training data. Latent space sampling can become a brush that empowers the artist, augments our creative affordances, and expands the space of what we can imagine [1,2]. This summer, the SIP mentor and interns wii work on a research project that aims at exploring how Recurrent Neural Networks (RNNs) can be used to generate sequence data. In this interesting and advanced deep learning project, the research group will study and implement a couple of most popular yet challenging and advanced tasks in natural networks. For example, the group will use RNNs, and specifically, LSTMs to generate human-like screenplays. Furthermore, the research group will use similar techniques to other types of sequence data, such as sequences of musical notes to generate new music, to time series of brush-stroke data (for example, recorded while an artist paints on an iPad) to generate paintings stroke by stroke, and so on.
[1] Chollet, Francois. Deep learning with Python. Simon and Schuster, 2021.
[2] Santhanam, Sivasurya. “Context based text-generation using lstm networks.” arXiv preprint arXiv:2005.00048 (2020).
Tasks:
To implement this research project, the high school SIP interns will learn various skills, tools, and concepts such as: (1) data mining; (2) advanced libraries and open-source platforms such as TensorFlow, Keras, and OpenCV; (3) designing and implementing advanced deep learning models; (4) using pre-trained models and getting familiar with transfer learning; (5) implementing advanced neural networks such as RNNs, GRUs, and LSTM; and (6) designing and implementing advanced and challenging projects such as text generation, music generation, and so on. The main applications of this research project include sentiment analysis, language modeling, speech recognition, and video analysis. This summer, the interns will learn designing and implementing a real-world application of deep learning models, specifically Recurrent Neural Networks and Long Short-Term Memory. To this end, the SIP interns will learn various deep learning concepts and tools — e.g., using the TensorFlow and Keras libraries, pre-trained models such as the MobileNet network, and popular online tools such as Google Colab and Jupyter notebook to solve programming problems. Furthermore, the interns will learn how to read research papers that have been published recently and implement them.
Required skills for interns prior to acceptance: None
URL: https://edgelab.ics.uci.edu
CSE-03: Implementing Neural Network from Scratch to Using Library (PyTorch)
Primary mentor: Pooneh Safayenikoo
UCSC faculty contact: Prof. Andrew Quinn
Location: 100% remote and online
Number of interns: 3
Project description:
Deep learning is the next wave of Artificial Intelligence (AI). it has a wide range of applications from image classification and speech recognition to natural language processing. Deep learning has also garnered a lot of attention recently in the context of small devices such as phones, robots, and self-driving cars. Artificial Neural Networks (ANNs) are used to solve highly non-linear problems like recognition, classification, and segmentation. The solution is mostly obtained using a network of deep convolutional and/or fully connected layers with many filters in each layer.
Tasks:
In this research project, the SIP interns will learn how neural networks work and how they can implement a simple neural network in Python. The interns will also learn how to build and deploy a real-world deep learning model application this summer. To achieve this goal, the interns will learn about numerous deep learning ideas and tools, such as the PyTorch libraries, pre-trained models from the small networks like LeNet-5 to bigger networks like ResNet, popular datasets like MNIST, and CIFAR datasets, and the use of GitHub and Jupyter notebooks to tackle programming challenges. The interns will also learn how to read research papers and put them into practice.
Required skills for interns prior to acceptance: Computer programming
CSE-04: Origami Robot: Modeling and Simulation
Primary mentor: Samira Zare
UCSC faculty contact: Prof. Mircea Teodorescu
Location: 100% remote and online
Number of interns: 3
Project description:
Deployable structures have gained increasing interest as potential alternatives to rigid structures in various applications where payload size is restricted. From solar panels used in space exploration to medical devices for minimally invasive surgeries, these innovative structures offer the ability to adapt and change their shapes based on their environment. For instance, solar origami panels can fold and compact for easy transportation, and then unfold and deploy to their final structure for maximum efficiency. The mentor’s research group is actively involved in the design, modeling, and development of deployable structures using Autodesk Inventor, a popular computer-aided design (CAD) software, and Python, a widely used programming language for scientific computing and data analysis. Through dynamical simulations in Autodesk Inventor and Python-based analysis, the mentor’s research group aims to gain insights into the movements and behaviors of deployable structures. This research project provides the SIP interns an opportunity to gain hands-on experience in the design, modeling, and analysis of deployable structures, utilizing cutting-edge software and programming tools. The SIP interns will work closely with the mentor’s research group and contribute to the advancement of knowledge in the field of deployable structures, while developing valuable skills in CAD, simulation, data analysis, and programming using Python.
Tasks:
The SIP interns’ specific tasks may include:
(1) Designing and modeling deployable structures using Autodesk Inventor, taking into account geometric configurations and kinematics;
(2) Developing dynamical simulations in Autodesk Inventor to replicate real-world conditions and environments, and observing the movements and behaviors of deployable structures under different scenarios;
(3) Using Python for data analysis of simulation results, including calculations of key parameters such as displacements;
(4) Generating visualizations, such as plots and animations, using Python to aid in the interpretation and communication of research findings;
(5) Collaborating with the research group to analyze and interpret the simulation data, and contributing to discussions and brainstorming sessions;
(6) Keeping up-to-date with the latest advancements in the field of deployable structures, and integrating new insights and techniques into the research work.
Required skills for interns prior to acceptance: None
CSE-05: Citizen Science Mobile Apps with Integrated Machine Learning Models
Primary mentor: Fahim Hasan Khan
UCSC faculty contact: Prof. Alex Pang
Location: 100% remote and online
Number of interns: 6
Project description:
Citizen science involves the participation of non-scientists in data collection according to specific scientific protocols and in the process of using and interpreting that data. Increasingly, citizen science platforms are going mobile with the growing power of mobile computation. The mentor’s research involves developing an open-source software platform that allows a domain researcher to quickly create a citizen science mobile app with integrated machine learning (ML) models for collecting data with real-time analysis. The mentor is currently working on creating ML-powered mobile apps and server-side infrastructures of the citizen science platform.
Tasks:
In this research project, the SIP interns will help the mentor to develop and test citizen science mobile apps and use them to collect data. The collected data will then be used for more training and optimization of machine learning (ML) models.
Required skills for interns prior to acceptance: None
URL: https://www.fahimhasankhan.com
CSE-06: Building Question Answering Models Grounded in Semantics
Primary mentor: Geetanjali Rakshit
UCSC faculty contact: Prof Jeffrey Flanigan
Location: 100% remote and online
Number of interns: 3
Project description:
With the current breakthrough in large language models such as ChatGPT, natural language processing (NLP) has garnered interest from people in all walks of life. NLP is about making computers learn language. It encompasses a lot of exciting problems like algorithms to teach a computer to translate input from one language to another, for example, English to French (machine translation), have a computer predict if a restaurant review written by someone is positive or negative (sentiment analysis), and so on. The goal of this research project is to build automated question answering systems/models grounded in semantics. The project will include working with existing rule-based models as well as state-of-the-art models to generate data for question answering, quality validation and evaluation of the generated data, as well as training models on this data on various kinds of model architectures.
Tasks:
The SIP interns working on this research project will help with data generation and working with deep learning models for question answering/reading comprehension tasks. The focus will be on analyzing these data, creating automated tests to check the quality of data, and using the data to train new models. The interns will learn to program in Python, work with real-world datasets, understand relevant concepts from natural language processing, and see these concepts in action by running state-of-the-art models. Based on the level of interest and preparedness of the interns, the mentor and interns may also do training of deep learning based models.
Required skills for interns prior to acceptance: None
URL: http://users.soe.ucsc.edu/~geet
CSE-07: Movement Data Animation
Primary mentor: Whitney Hansen
UCSC faculty contact: Prof. Chris Wilmers
Location: 100% remote and online
Number of interns: 3
Project description:
The purpose of this research project is to explore new and descriptive methods of animating and visually presenting movement data. The mentor is analyzing African wild dog GPS data for multiple research projects, and needs help investigating the newest R packages and visualization techniques that can showcase their research. This research project will involve learning how to process animal GPS data, utilize R and RStudio to handle and manipulate data, researching methods of data visualization, and learning plotting and graphics. While the mentor has a strong background in coding and GPS data visualization, they do not know what packages are out there or the best way to visualize their data yet. This research project is for independently motivated, problem-solving interns who are willing to execute tasks on their own initiative and think outside the box. Ideally, these interns have a strong interest in wildlife/conservation, science communication, and coding in R.
Tasks:
The high school SIP interns will:
—Process GPS movement data in R;
—Carry out data wrangling in R;
—Research R packages for data visualization;
—Test animation techniques for GPS data;
—Troubleshoot R packages on example data; and
—Create figures, movies, and other visualization graphics demonstrating key wild dog movement processes.
Required skills for interns prior to acceptance: Computer programming
URL: kwhitneyhansen.com
CSE-08: Applicable Data Analysis: From Scratch to Hatch
Primary mentors: Li Liu, Zichao Li
UCSC faculty contact: Prof. Yuyin Zhou
Location: 100% remote and online
Number of interns: 3
Project description:
The primary objective of this research project is to offer interns a comprehensive introduction to data analysis, covering the fundamental areas of data collection, data processing, and data visualization. Each module of the project will feature a lecture-style presentation followed by hands-on exercises, allowing participants to put the concepts and techniques learned in the presentation into practice. The project will also provide tutorials on popular data analysis tools like Python and Excel. In addition to the lectures and exercises, the research project will provide opportunities for the high school SIP interns to create their own data analysis applications. This will allow the interns to apply their skills and creativity in practical and innovative ways. The interns will be encouraged to explore their areas of interest, such as climate change, healthcare, social media computing, and more, and apply data analysis techniques to solve real-world problems. Overall, this research project will equip interns with essential data analysis skills and provide them with an opportunity to apply these skills in a practical setting. By the end of the research project, the interns will have a better understanding of data analysis and the ways it can be used to tackle real-world challenges.
Tasks:
The high school SIP interns will:
(1) Learn basic data analysis tools;
(2) Identify real-world problems where data analysis can help; and
(3) Implement a demo solution using data analysis techniques.
Required skills for interns prior to acceptance: None
URL: https://leolee7.github.io/
CSE-09: Event-Centric Reasoning with Large Language Models
Primary mentor: Rongwen Zhao
UCSC faculty contact: Prof. Jeffrey Flanigan
Location: 100% remote and online
Number of interns: 3
Project description:
Natural language processing (NLP) helps machines interact with humans in natural language and perform language-related tasks. Recently, a series of large language models (LLMs) created by OpenAI has attracted a great amount of attention not only from the NLP community, but also the other fields. They have been shown to be able to solve various NLP tasks, even requiring human-level reasoning. Although with the remarkable advances of LLMs, reasoning about events and the state of entities with the dynamic contexts remains challenging since models need to figure out the required implicit information and related commonsense knowledge of these events and entities. The goal of this project is to annotate an event-centric reasoning dataset and evaluate the annotated dataset with LLMs.
Tasks:
The SIP interns working on this research project will help the mentor annotate a high-quality event-centric reasoning dataset that requires various commonsense knowledge. The annotated dataset will be used for fine-tuning a pre-trained model or evaluating the capability of the recently released LLMs. The interns will learn to program in PyTorch and other deep learning libraries. The interns will learn how to fine-tune pre-trained models and design prompting techniques for LLMs.
Required skills for interns prior to acceptance: None
CSE-10: Computer Vision: Indoor Spatial Understanding
Primary mentor: Yunqian Cheng
UCSC faculty contact: Prof. Roberto Manduchi
Location: 100% remote and online
Number of interns: 3 + TSIP
Project description:
This is a research project on indoor spatial understanding using computer vision. This research project is designed to introduce the high school SIP interns to the exciting field of computer vision, with a particular focus on indoor spatial understanding. Through a combination of lectures, exercises, and participation in a real research, the interns will gain a comprehensive understanding of the fundamental concepts and techniques involved in this area. In the first module of this research project, the interns will learn about edge detection, projective geometry, image processing, as well as data collection and analysis. The interns will also gain exposure to popular tools like Python and OpenCV. The lectures will be followed by hands-on exercises that will enable the interns to put their newly acquired knowledge into practice. In the second module of the research project, the interns will contribute to collecting and labeling video data that will be used to train machine learning algorithms for geometric reconstruction. Throughout the research project, the interns will be encouraged to explore their interests and apply their newly acquired skills to real-world problems. By the end of the research project, the interns will have a deeper understanding of computer vision and will be able to apply their skills to tackle real-world challenges related to scene understanding and image analysis. The interns will also have developed valuable skills in problem-solving, critical thinking, and collaboration that will serve them well in their future academic and professional pursuits.
Tasks:
The SIP/TSIP interns will:
—Learn basic computer vision through lecture and exercises;
—Perform data collection online or using smart phone cameras;
—Learn how to use simple data processing tools/scripts (Python knowledge will be greatly appreciated); and
—Use labeling tools to generate high-quality annotations.
Required skills for interns prior to acceptance: None; computer programming experience in Python is highly recommended
URL: https://583482035.wixsite.com/home
CSE-11: Exploring the Limitations and Pragmatic Usages of the New Bing Search
Primary mentor: Changmao Li
UCSC faculty contact: Prof. Jeffrey Flanigan
Location: 100% remote and online
Number of interns: 3
Project description:
The new Bing search, combined with ChatGPT, promises to deliver improved search results and a better user experience. However, there can be factually incorrect results, and users may not know how to effectively query it to obtain better results. This research project aims to investigate the limitations and pragmatic uses of the new Bing search. Specifically, the SIP mentor and interns will examine the following research questions: (1) How can ChatGPT augment the traditional Bing search by overcoming some of its limitations, particularly in terms of providing personalized and contextualized responses? (2) After augmentation with ChatGPT, what are the limitations, particularly in terms of inaccurate/incorrect search results or making up factual content, or other limited capabilities? (3) In what conditions should users choose to use the new Bing search instead of traditional search engines such as a Google search? and (4) How can users use the new Bing search wisely in the sense of constructing better queries?
Tasks:
The SIP interns will collect search queries from a diverse set of use cases and topics and apply these queries on Google search, the traditional Bing search, and the new Bing search and obtain the outputs. The interns will analyze the results in detail in order to answer first three of the above questions. The interns will then systematically investigate the design of queries for the new Bing search, and come up with recommendations for its effective use.
Required skills for interns prior to acceptance: None
CSE-12: Quantum Secret Key Agreement
Primary mentor: Archana Singh
Secondary mentor: Xinyi Wu
UCSC faculty contact: Prof. Zouheir Rezki
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Quantum secret key agreement is a secure communication protocol that uses quantum mechanics to create a shared secret key between two parties. The protocol involves the exchange of qubits, which cannot be measured without being disturbed, ensuring that any eavesdropping attempts are detected. The matching qubits are then used to generate a shared secret key that can be used with symmetric encryption algorithms to encrypt messages. This ensures that only the intended recipient can decrypt and read the message, making it secure against interception. Quantum secret key agreement is a promising technology for secure communication in the age of quantum computing.
Tasks:
Through this research project, the SIP interns will learn the basic principles of quantum communication that set it apart from any classical communication, providing better data security. The interns will learn to read academic papers in the field effectively and to turn their ideas into research work using mathematical modeling and Qiskit programming (a package in Python for quantum computing).
Required skills for interns prior to acceptance: None
CSE-13: Deep Learning – Model Pruning for Deployment
Primary mentor: Sathyaprakash Narayanan
UCSC faculty contact: Prof. Jason Eshraghian
Location: 100% remote and online
Number of interns: 3
Project description:
The Convolutional Neural Network (CNN) is a highly effective deep learning architecture designed primarily for image recognition and classification tasks. In recent years, there has been a surge in the complexity and size of CNN models, which has led to increased computational requirements and resource consumption. To address these challenges, this research project aims to study and develop efficient techniques for training and pruning CNN models without compromising their accuracy and performance. Training and pruning CNN models can lead to smaller, faster, and more energy-efficient networks, which are highly desirable in edge devices and real-time applications. Model pruning involves the removal of redundant neurons or connections in the network, which reduces the overall model size and computational requirements. Various pruning techniques, such as weight pruning, neuron pruning, and filter pruning, will be explored in this research project.
Tasks:
The SIP interns’ tasks will include: (1) Python programming every week; (2) exploring machine learning (ML)/deep learning (DL) frameworks such as Pytorch; (3) data augmentation (4) critical reading of research papers; and (6) DL model building. The interns will compare the results of model pruning, quantization, and knowledge distillation.
Required skills for interns prior to acceptance: Computer programming
URL: https://satabios.github.io/
CSE-14: Studying and Applying Decentralized Edge Intelligence to Real-World Applications
Primary mentor: Harikrishna Kuttivelil
UCSC faculty contact: Prof. Katia Obraczka
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Edge intelligence is a growing paradigm of artificial intelligence (AI). Instead of utilizing large, central entities (such as data and compute centers like Google, Facebook, Microsoft, etc.) as is done in most modern AI, edge intelligence is about how we can move AI systems and algorithms closer to the “edge of the network”, i.e., the devices at the very end of the network such as our phones, tablets, other consumer devices, sensors, etc. Edge intelligence systems must consider the numerous constraints of these limited devices and environments, execute their processes efficiently in the face of dynamic environments, and retain the performance of larger, more performant systems. In this research project, the mentor’s research group is focused on the application of decentralized and clustered edge intelligence to real-world applications around us. However, in order to do so, the group must be able to model these real-world situations. In this research project, the SIP mentor and interns will study interesting applications and find datasets to properly model them. The group will learn and utilize data pre-processing to make those datasets useful to use. The group will create ML/AI models to learn from that processed datasets. Finally, the group will use existing edge intelligence frameworks to observe how edge intelligence can help or hurt these selected applications.
Tasks:
The SIP interns will: (1) analyze existing research works on edge intelligence and applications; (2) identify key features of edge intelligence systems and map them onto potential application scenarios in which edge intelligence can be applied; (3) identify potential application scenarios to deploy edge intelligence in and find relevant datasets; (4) pre-process their discovered datasets such that they can develop and train ML/AI models; (5) use existing frameworks to take their ML model and data and apply it to in the context of edge intelligence and observe the behaviors of the resulting system; and (6) analyze the performance of resulting edge intelligence systems and draw conclusions about the effectiveness of their application scenarios.
Required skills for interns prior to acceptance: Computer programming
CSE-15: 3D Human Face Capture and Reconstruction
Primary mentor: Jiahao Luo
UCSC faculty contact: Prof. James Davis
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Three-dimensional (3D) human face models find a wide range of applications in scenarios such as 3D avatars, biometric identification, photo editing, and film production. The main propose of this research project is to help with 3D human face reconstruction and visualization.
Tasks:
In this research project, the SIP interns will learn the basic principles of state-of-the-art 3D human face technology. Depending on their experience and interests, the interns will also get involved in some subset of the following: 3D data capture, synthetic data generation, face model reconstruction, 3D rendering, and/or animation.
Required skills for interns prior to acceptance: Computer programming, statistical data analysis
CSE-16: Image Classification Using Grad-CAM
Primary mentor: Sijia Zhong
UCSC faculty contact: Prof. Leilani Gilpin
Location: 100% remote and online
Number of interns: 4
Project description:
Image classification is a supervised learning problem: one defines a set of target classes (objects to identify in images) and trains a model to recognize them using labeled example photos. Image classification is a great example of machine learning and includes many steps — e.g., preparing datasets, training, and testing. The SIP interns will create an image classifier in order to deepen their understanding of machine learning project. After creating an image classifier, the interns will be introduced to a tool named Grad-CAM. The Grad-CAM technique utilizes the gradients of the classification score with respect to the final convolutional feature map, to identify the parts of an input image that most impact the classification score. This task will help the SIP interns visualize how the image classifier works.
Tasks:
In this research project, the SIP interns will learn how to create an image classifier and apply the Grad-CAM techniques to the classifier. The interns will carry out the following tasks: (1) prepare a dataset; (2) train and save a model; (3) test the model; and (4) apply Grad-CAM to the model. The SIP interns will use Python for the coding tasks. If needed, this research project will start with a basic tutorial on Python.
Required skills for interns prior to acceptance: Computer programming
URL: https://github.com/szhong16/classifier_exercise
CSE-17: Deep Learning Algorithms for 3D Reconstruction of Stem Cells
Primary mentor: Hamed Tangestani
UCSC faculty contact: Prof. Ali Shariati
Location: 100% remote and online
Number of interns: 3
Project description:
The comprehensive understanding of molecular spatial statistics in organoids is crucial for gaining insights into the intricate cellular processes and for the advancement of regenerative medicine. Given the inherent complexity, conventional methods fall short, prompting the need for innovative approaches. This research project intends to fulfill this need by utilizing deep learning models for precise segmentation of stem cells in microscopic images, followed by their 3D reconstruction. This approach enables the mentor’s research group to decipher the intricate spatial distribution and organization of stem cells within organoids. Thus, through the intersection of deep learning and 3D visualization, the mentor’s research group aims to bring new depths to the understanding of molecular spatial statistics.
Tasks:
In this research project, the mentor will introduce the SIP interns to the mathematical concepts underlying deep learning. Through Python, step by step, the mentor and interns will construct a deep learning model for biomedical images in stem cell organoids.
Required skills for interns prior to acceptance: Computer programming
CSE-18: Scaling Python and Machine Learning Applications with the Ray Framework
Primary mentor: Soroush Zare
UCSC faculty contact: Prof. Andrew Quinn
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Machine learning (ML) is a set of techniques that allow computers to learn specific tasks. With the new wave of artificial intelligence (AI) and ML applications, it is becoming more challenging to have solutions that work as the workload gets bigger. One way to make such applications scalable is to distribute the workload to different workers, each of which might run on a different computer core to allow parallelization, which can in turn greatly increase the speed.
Tasks:
In this research project, the SIP interns will learn about the Python programming language and the Ray framework (available for Python) which is used to scale Python and AI workloads. The mentor and interns will go through the process of setting up Ray, discuss how it works internally, and also see examples of programs integrated with Ray to allow speedups. The SIP interns will also be assigned some problems to write in Python and incorporate them with Ray to ensure they can apply the concepts they have learned.
Required skills for interns prior to acceptance: Computer programming
CSE-19: Applying Reinforcement Learning Algorithms in Simulated Car Lane Following
Primary mentor: Oliver Chang
UCSC faculty contact: Prof. Leilani Gilpin
Location: 100% remote and online
Number of interns: 3
Project description:
Deep reinforcement learning (DRL) is becoming an increasingly powerful way to train intelligent agents to achieve complex tasks. Reinforcement learning (RL) is a branch of machine learning that teaches an agent through rewards or punishments through interactions in an environment. In particular, policy gradient (PG) methods are promising in autonomous driving because they do not need well-annotated data. Instead, they use a convolutional neural network as a controller and update the parameters based on the reward outcome from the environment. However, PG methods are unstable and take a long time to train. The mentor is interested in applying a potentially better PG algorithm called proximal policy optimization (PPO) to various DRL tasks. Implementing PPO to a wide array of RL tasks like playing Pac-Man, spider walking, and car racing would solidify PPOs promise as a stable PG algorithm.
Tasks:
The first task for the SIP interns is to pick a gym environment that they find interesting. Gym is a Python extension that makes it easy to access myriad environments like Atari games, physics tools, and 3D motions like spider-walking. Then, the interns will play around with an environment of their choice and report what is included; what do the rewards and states look like? Next, the SIP interns will implement and assess a simple PG algorithm. Finally, the interns will apply the PPO algorithm and see if there is improvement over the simple algorithm.
Required skills for interns prior to acceptance: Computer programming, statistical data analysis
Digital Arts and New Media
DAN-01: Finding Norma: In Search of Feminist Media Archives From the 1970s
Primary mentor: Livia Perez
UCSC faculty contact: Prof. Mark Nash
Location: 100% remote and online
Number of interns: 4
Project description:
Feminist videos, short films, home movies, still works, and alternative formats are less known in audiovisual historiography than mainstream pieces such as feature films. The precariousness resulting from the radical choice of media (e.g., first generation videotapes) or the innumerable obstacles in conserving these works makes us unaware of a large part of these images, particularly those produced by queer and black artists and activists. In this research project, the SIP mentor and interns will go over film archives to mine from the feminist movement in the United States during the 1970s. Through this research project, the SIP interns will receive training on several aspects of archival material research for documentary filmmaking such as crafting a narrative, pre-production planning, and still and moving image editing. Additionally, the SIP interns will be taught methods for conducting non-fiction research and archival research. The archives have extensive, diverse research materials, such as photographs, film footage, newspapers, online articles, paintings, letters, journals, and diaries.
Tasks:
In this research project, the SIP interns will collaborate on excavating archival research (films, videos, photographs, documents and papers) to develop an artistic curatorial project that will unfold in a future exhibition and a documentary feature film. These materials and data will complement the archival research on neglected media, especially those produced by women, queer, and BIPOC people, that the mentor of this research project has been doing for the last three years.
Required skills for interns prior to acceptance: Computer programming, field work
Earth and Planetary Sciences
No research projects posted yet.
Ecology and Evolutionary Biology
EEB-01: The Role of Oxytocin in Social Competence
Primary mentor: Megan Molinari
UCSC faculty contact: Prof. Suzanne Alonzo
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Oxytocin is a hormone that is involved in social interactions across diverse animal groups including fish, amphibians, birds, and mammals. Despite being very important in social interactions, the way oxytocin works is still debated due to the differing effects oxytocin can have on animal behavior- sometimes increasing cooperation while in other cases increasing aggression towards other individuals. One theory behind the influence of oxytocin is that it may help animals pay attention to the social cues of their peers, allowing them to make the appropriate social decision (which is known as social competence). This project will test the impact of oxytocin on the behavior of a fish species with complex social behavior, the ocellated wrasse (Symphodus ocellatus), to see if it increases social competence in this species.
Tasks:
Male ocellated wrasse form complex social relationships during the reproductive season, in which two individuals form temporary relationships where they have to balance competition and cooperation. The mentor will record the social interactions between pairs of male ocellated wrasse in the wild. The mentor will then inject oxytocin into one individual in this relationship and take another recording of the social interactions between the two males. The SIP interns will help the mentor analyze this behavioral footage, learning skills on how to define and measure animal behavior. The mentor and interns will then analyze this behavioral data to determine if oxytocin helps the male ocellated wrasse make the appropriate decision given the social cues they receive, learning skills in statistical analysis and R code.
Required skills for interns prior to acceptance: None
EEB-02: Diving Performance of Semi-Aquatic Garter Snakes Over Ontogeny
Primary mentor: Elsie Cecilia Carrillo
UCSC faculty contact: Prof. Rita Mehta
Location: 100% remote and online
Number of interns: 3
Project description:
Garter snakes are excellent models for studying the physiology, behavior, and evolution of a semi-aquatic lifestyle. Some garter snakes experience ontogenetic shifts in their foraging ecology, feeding on more aquatic prey as they grow. The mentor’s research group is interested in investigating if garter snake diving performance changes over ontogeny in two species of garter snakes, one more aquatic and the other more terrestrial. The SIP mentor and interns will analyze video footage for three experimental assays: (1) breath-hold ability, (2) bradycardic response, and (3) swim speed/proportion of surface swims/dives. This research will help the mentor’s group understand what it takes to be semi-aquatic.
Tasks:
The SIP interns will analyze video footage for two species of garter snakes across three experimental assays for the first two years of life. For the first assay “breath-hold ability,” the intern will record the maximum submergence time in seconds. For the second assay, the intern will log time and heart rate in a “simulated dive” where the head of the garter snake is submerged while a fetal doppler is placed over the heart. In the third assay, the intern will analyze swimming speed using the program Tracker and also log the proportion of surface swims to dives over a two-minute period in a small wading pool. The interns will also learn how to take snake measurements using the software Serpwidget.
Required skills for interns prior to acceptance: None
URL: https://mehta.eeb.ucsc.edu/
No research projects posted yet.
Economics
No research projects posted yet.
Electrical Engineering
ELE-01: Learning-Based Framework for Heart Disease Identification
Primary mentor: Xinyi Wu
UCSC faculty contact: Prof. Zouheir Rezki
Location: 100% remote and online
Number of interns: 3
Project description: Computer-assisted test interpretations have efficiently supported doctors in addressing early diagnosis of heart disease during routine examinations. In particular, an electrocardiogram (ECG), one of the most popular cardiac tests, is a quick and painless tool for early diagnosis. It presents the status of the patient’s heart condition, depending on precision of test interpretation. The objective of this research project is to substantially enhance heart disease identification via a comprehensive learning-based framework leveraging physical tests such as ECG test, cardiac stress test, etc.
Tasks: This research project will be conducted using Python programming software. The SIP interns will:
(1) Gain knowledge about an electrocardiogram (ECG);
(2) Learn about signal processing methods, machine learning, and deep learning;
(3) Develop a detection model for ECG signals;
(4) Develop a multi-label classification model based on deep learning methods; and
(5) Develop a multi-label forecasting model based on deep learning methods.
Required skills for interns prior to acceptance: Computer programming, statistical data analysis
ELE-02: Decentralized Energy Management in Smart Grids
Primary mentor: Fargol Nematkhah
UCSC faculty contact: Prof. Yihsu Chen
Location: 100% remote and online
Number of interns: 3
Project description:
High penetration of distributed energy resources (DERs) such as photovoltaic (PV) panels into electric grids along with the proliferation of new loads such as electric vehicles are challenging the traditional methods of operation and transforming the conventional grid into a cyber-physical system called the smart grid. Accordingly, the distributed nature associated with DERs calls for distributed management schemes where resource owners would be able to make decisions autonomously while satisfying the grid’s needs such as supply-demand balance and transmission lines’ capacity. To get a glimpse of how such schemes might work, consider the scenario where a PV panel has created more power than expected for the next five minutes; the surplus power can be used by another consumer at a different location who is in need of power while respecting the operational constraints of the grid. This method of power provision unburdens the electric grid and offers economic opportunities for resource owners. This summer, the SIP interns will gain insight on the basic principles of electric grid operation and get familiar with the classic and novel optimization problems in the context such as economic dispatch, unit commitment, and optimal power flow. They will learn to effectively read academic papers of the field and to transform their ideas into research work through mathematical modeling and computer programming.
Tasks:
The SIP interns’ tasks/summer research experience will include;
(1) Basic principles of operation and energy management in electric grids;
(2) Electricity markets and the governing economic mechanisms;
(3) Novel transformations in energy sector and the smart grid concept;
(4) Basics of optimization and mathematical modeling;
(5) Optimization programming;
(6) Critical literature review; and
(7) Effective collaboration in research teams.
Required skills for interns prior to acceptance: None
URL: https://people.ucsc.edu/~ychen225/
ELE-03: Finite Element Simulation of Fluorescent Dielectric Nanoparticle Trapping Under the Influence of Electrostatic Field and Their Corresponding Fluorescence Signal Extraction for Biosensing Quantification.
Primary mentor: K B M Rakib Hasan
UCSC faculty contact: Prof. Ahmet Ali Yanik
Location: 100% remote and online
Number of interns: 4
Project description:
Fluorescence-based disease detection techniques have been in the heart of the conventional disease diagnostics. Different clinical diagnostic tools like ELISA, RT-PCR, digital ELISAs use fluorescence-based modality for biosensing quantification. On the other hand, electrophoresis and dielectrophoresis are among the most popular particle trapping methods capable of trapping different polarized/nonpolarized bioparticles on sensor surfaces. Interdigitated electrode (IDE) is the one of the most used sensors for an electrophoretic/dielectrophoretic fluorescent bioparticle trapping, which provides a periodic fluorescence readout convenient for target quantification. In this project, the interns will be guided to obtain an optimum IDE geometry using a finite element method-based simulation tool in order to achieve a high signal-to-noise ratio in the fluorescence readout. The mentor’s research group has invented a fluorescence-based bioparticle detection technique using electrophoretic trapping of dielectric nanoparticles followed by a digital image processing-based algorithm for their quantification from the raw fluorescence images taken via epifluorescence imaging. During the last part of the project, the SIP interns will be guided to learn the conventional image processing toolboxes like ImageJ and MATLAB used for background subtraction and signal extraction for quantification.
Tasks:
The SIP interns will: (1) learn COMSOL Multiphysics for finite element method-based modeling of an electrophoretic nanoparticle trapping on IDE surface; and (2) learn ImageJ and MATLAB for post-processing and signal extraction from the raw fluorescence images.
Required skills for interns prior to acceptance: None
URL: https://www.yaniklab.science/home
ELE-04: Modeling of Biosensors and Performance Analysis
Primary mentor: Kamrun Nahar Shushama
UCSC faculty contact: Prof. Ahmet Ali Yanik
Location: 100% remote and online
Number of interns: 3
Project description:
Biosensors are playing important role in early stage disease detection. They are used in many industry applications, such as medical diagnostics like, Covid- 19 detection, enzyme detection, food safety, environmental monitoring etc. There are different types of biosensors based on their working principle e. g surface plasmon resonance based biosensor, electrochemical based biosensor, nanopore based biosensor, fluorescence based biosensor etc. These biosensors are used depending upon their application areas and the advantages they are providing. In this project, we will do literature review of different types of biosensors, learn their advantages and limitations. Then we will do modeling of one type of biosensor; how to do modeling, performance analysis. We will get introduced with softwares like MATLAB and COMSOL for modeling and performance analysis.
Tasks:
The SIP interns will work on the design of a biosensor. The interns will do literature review of different types biosensor, learn about transfer matrix method, learn MATLAB and COMSOL software simulation.
Required skills for interns prior to acceptance: None
ELE-05: Analytical Performance Analysis of Nanopore Sensors
Primary mentor: Reefat Inum
UCSC faculty contact: Prof. Ahmet Ali Yanik
Location: 100% remote and online
Number of interns: 3
Project description:
The nanopore field has made great strides over the past twenty years, starting with the detection and characterization of biomolecules ranging from nucleic acids to protein complexes. One high-impact prospect that has only recently started to be addressed is the potential for nanopores to provide a platform for disease biomarker identification and quantification from clinical samples. In comparison to their biological counterpart, solid-state nanopores hold great promise in this type of application because of their mechanical robustness and durability due to suitable supporting membranes, tunable pore size and geometry to fit various targets of interest, and ease of integration with customizable flow-cells and precision current amplifier. However, detection and quantification of target protein biomarker using solid-state nanopores isn’t without any challenges. To achieve the best signal-to-noise ratio (SNR), it’s important to optimize the ratio of pores to particles, as well as the electrolyte solution’s conductivity, pH, viscosity, and other factors. Additionally, it’s necessary to adjust the pore geometry and surface charge of the target analyte to ensure enough translocation events occur within a short timeframe. The mentor’s research group is working on developing a high throughput nanopore sensor. The interns will work on the analytical modelling with the mentor to optimize the parameters for the experimental protocol.
Tasks:
The SIP interns will have three main tasks: (1) learn about the working principles and applications of nanopore sensors; (2) gain a fundamental understanding of how to mathematically model a nanopore sensor; and (3) use the analytical model to carry out performance analysis and determine the optimal sensor design parameters. During this process, the interns will also be introduced to the basics of MATLAB programming and the COMSOL software.
Required skills for interns prior to acceptance: None
URL: https://scholar.google.com/citations?hl=en&user=V3woP9sAAAAJ
Environmental Studies
ENV-01: Monitoring in the Santa Cruz Mountains
Primary mentor: John Morgan
UCSC faculty contact: Prof. Chris Wilmers
Location: 100% remote and online
Number of interns: 3
Project description:
Camera traps are an important tool for wildlife research and conservation. Camera traps enable researchers to detect the presence of elusive species, estimate population sizes, and record behaviors that would otherwise be nearly impossible to observe. In the Santa Cruz Mountains camera traps are used to remotely monitor the presence of wildlife species, including mountain lions and their prey. This summer, interns will help the Santa Cruz Puma Project process images collected from camera traps deployed in a grid across the Santa Cruz Mountains. Interns will help calculate the relative abundance of species in the study area and make predictions about how environmental and anthropogenic factors affect species abundances.
Tasks:
The SIP interns will primarily be responsible for identifying species present in photos captured using camera traps deployed in the Santa Cruz Mountains. The interns will gain experience managing and processing data and performing basic analyses to estimate species abundance and temporal patterns. The interns will then explore how these patterns might change spatially based on environmental and anthropogenic factors.
Required skills for interns prior to acceptance: None
Film and Digital Media
FDM-01: Tuning in – Reading Works in Sound and Moving Image
Primary mentor: Merve Genç
UCSC faculty contact: Prof. Yiman Wang
Location: 100% remote and online
Number of interns: 3
Project description:
This research project focuses on a body of contemporary artworks from the last five decades, considering how sound and moving images have been used to tune into the world that we live in. Using a variety of writing and critical reading skills, the group will be producing a body of writing on artworks selected by the mentor, to be complemented by works that the SIP interns will bring in, to produce a body of writing in which the group will have engaged with the specific qualities of each work while connecting these works to the larger historical and social structures in which they emerged.
Tasks:
The SIP interns will: (1) conduct historical and social research surrounding artworks; (2) write on artworks; (3) give feedback on writing; (4) engage in weekly discussions; and (5) contribute with artworks of their own choosing.
Required skills for interns prior to acceptance: None
URL: https://film.ucsc.edu/people/merve_unsal; https://merveunsal.com/
History
HIS-01: History from Below and to the Left
Primary mentor: Carlos Cruz
UCSC faculty contact: Prof. Grace Peña Delgado
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Is history an objective study where the historian is far removed from the object of study? The writing of history, whether scholars want to acknowledge it or not, is deeply conditioned by political, personal, and moral conditions along with the temporal and spacial conditions that shape our lives. Historians as writers take stands by choosing certain words, vocabulary, and choice of evidence, along with conceptual categories. More importantly, however, are the silences and omissions. What does it mean to do history from below and to the left? Drawing from histories that refuse to objectify communities of struggle, this research project will explore how historians can construct stories based on narratives that revolve around feeling and thinking, that centers the autonomy of the individual as well as the communities that shape their lives and push back on oppressive racial patriarchal capitalist conditions. The SIP mentor and interns will discuss and consider the aims and methods of social history along with class, gender, and race in order to determine what history from below and to the left can look like for the research group, especially as it relates to the Mexican Revolution of the 20th century.
Tasks:
The SIP interns will read primary historical sources about gender, class, labor struggle, and its intersection with Indigenous peoples. The interns will learn to retrieve scholarly journals and write critical reviews. Moreover, the SIP interns will assist the mentor with identifying key texts through digital archives and classifying them. This task will teach the interns to engage and analyze digital archival research as a historical methodology. The SIP interns will have an opportunity to engage in their own personal histories research mini-project by utilizing historical databases to create their own “histories from below and to the left.” The mentor will encourage the interns to present their findings to one another to encourage the practice of the everyday public historian.
Required skills for interns prior to acceptance: None
Latin American and Latino Studies
LAL-01: Kids and Care Work: Latinx Mixed-Status Family Affective Landscapes and Children’s Emotional Labor
Primary mentor: Karina Ruiz
UCSC faculty contact: Dr. Jessica K. Taft
Location: 100% remote and online
Number of interns: 3
Project description:
This research project analyzes newly collected original qualitative data including participant observations, interviews, and focus groups. Completing initial coding and analysis, the SIP interns will learn about how children in Latinx mixed-status families learn and practice emotional labor skills across home and community contexts.
Tasks:
The SIP interns will work on literature review, qualitative coding, and qualitative analysis.
Required skills for interns prior to acceptance: None
Linguistics
LIN-01: The Phonetics of Voice in Santiago Laxopa Zapotec
Primary mentor: Mykel Brinkerhoff
UCSC faculty contact: Prof. Grant McGuire
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
In order to gain an understanding of what is possible in human languages, linguists often conduct linguistic fieldwork. This fieldwork consists of collecting wordlists, stories, sentences, and grammatical judgements. This project is concerned with probing questions about what sounds exist in the world’s languages and how these sounds interact with each other. One such research question has to do with what phonetic principles determine how these sounds are organized in the minds of speakers to the exclusion of other sounds. This research project will be using data collected during the summer of 2022 to investigate what are the characteristics that define the different types of vowels in Zapotec. In Zapotec, each vowel appears with one of four different modes or voice qualities: breathy, checked, laryngealized, and model. Depending on which voice quality is used, this can indicate whether one is talking about fish or snakes (bal vs. bahl) or a marketplace or a rifle (ya’a vs. yah). Preliminary research seems to indicate that only two acoustic measurements are necessary to differentiate the four voice qualities. This research project will determine if those acoustic measurements are the only acoustic measurements that are necessary to classify the different voice qualities.
Tasks:
The SIP interns will be asked to assist with annotating and analyzing audio recordings collected from 18 native speakers of Santiago Laxopa Zapotec. This will consist of the interns learning: (1) how to segment audio into meaningful parts; (2) measure meaningful acoustic information; and (3) how to annotate the audio files, and (4) how to perform statistical analyses on those measurements. Additionally, the interns will learn how to maintain and enter information into a corpus designed to facilitate phonological and phonetic analyses. While completing these tasks, the interns will learn what linguistics is and some of the areas of human language that linguists explore.
Required skills for interns prior to acceptance: Statistical data analysis, field work
Literature
LIT-01: Mapping Queer and Feminist Literary Montreal
Primary mentor: Arielle Burgdorf
UCSC faculty contact: Prof. Carla Freccero
Location: 100% remote and online
Number of interns: 3
Project description:
Montreal has a rich history of queer and feminist meeting places, but unfortunately many of them no longer exist. However, traces of these underground spaces remain in the literature of Montreal, which depicts cafes, lesbian bars, salons, and bookstores that served as points of connection, creation, and liberation for women during the 1980s and 1990s. This project will create a cartography of queer and feminist spaces in Montreal in the 1980s and 1990s through its francophone and anglophone literature. Possible authors might include: Nicole Brossard, Gail Scott, Marie-Claire Blais, Louky Bersianik, and France Théoret. The end result will be a visual representation of different annotated areas from queer and feminist history found in novels and short stories from Montreal, chosen based on each intern’s interests. The research project also brings up the issue of linguistic divisions and segregation within subcultures. The map acts as a queer, intersectional intervention into normative time and gentrification, providing a window into a transgressive past and offering ideas to inform the city’s future.
Tasks:
The SIP interns will have the opportunity to research the history of queer and feminist spaces in Montreal through the lens of literature, identify relevant literary materials within a specific timeframe (1980s-1990s), read literature with a critical eye towards data collection, determine which primary sources are reliable and trustworthy for research, search library resources/databases, gain a familiarity with archival science, create annotated bibliographies, gain a familiarity with citation programs such as Zotero, (if possible) read materials in English and French and/or translate relevant sections of the materials, use map-reading skills to identify the locations of former queer and feminist spaces, add data findings to a collective map using programs or software such as ArcGIS StoryMaps, pinpoint important geographic spaces and provide accompanying annotations of each data point, and respond to/be in conversation with the other interns while sharing information with one another.
Required skills for interns prior to acceptance: None
LIT-02: Translating and Adapting the World of Hunter x Hunter
Primary mentor: Zoë Sprott
UCSC faculty contact: Prof. Renée Fox
Location: In person/hybrid on the UCSC campus
Number of interns: 4
Project description:
This research project analyzes Yoshihiro Togashi’s manga and anime series Hunter x Hunter in its various adaptations and English translations. The goal of this research project is to better understand how Togashi engages in world-building and how his worlds have been translated across texts. The SIP interns will engage with one version of Hunter x Hunter, provide notes and observations, and work together to highlight similarities and differences among the texts. Working closely with their mentor, the interns will also have the opportunity to focus on particular aspects of Hunter x Hunter, such as fashion, gender, or immigration, and explore them in more depth.
Tasks:
The SIP interns will be assigned one version of Hunter x Hunter to read/watch and are responsible for taking comprehensive notes on their observations, reactions, and questions. Together with the mentor, the interns will engage in group discussions around the many versions of the text. Individually (with guidance from the mentor), each intern will develop a specific area of interest within the text, which they will have the opportunity to explore in more depth. No language fluency outside of English is required, but Japanese language learners are especially encouraged to apply.
Required skills for interns prior to acceptance: None
URL: https://literature.ucsc.edu/
LIT-03: The Experience of Chronic Pain and the “Pain Gap” in Western Medical Practice
Primary mentor: Katherine Rogers
UCSC faculty contact: Prof. Hunter Bivens
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
It can take 6 or more visits and 8 or more years to be diagnosed with endometriosis, a chronic pain condition affecting, by some estimates, 1 in 10 people who menstruate. Those facing the pain are often told the pain is in their heads before they are taken seriously. This example shows a persistent problem in Western medicine – that some people’s pain is believed and responded to with treatment, and some are not (a phenomenon commonly known as the “pain gap”). This research project takes a multidisciplinary approach to questions of pain and agency. It interacts with fields like medical anthropology and disability studies to better understand what types of pain are taken seriously in medical practices today. This is an especially important question for certain marginalized identity groups, including women, people of color, and trans people, who often face medical discrimination. Research questions include: Whose pain is listened to and treated and why? What does chronic pain do to the body and the conception of the self?
Tasks:
The SIP interns will get a grounding in concepts like the “pain gap” and the history of medicine (especially gynecology) and will work with the mentor to develop a research agenda that includes medical studies, theoretical texts, and “life writing” to answer a targeted research question. To foster independent research skills, each intern will choose a different chronic pain diagnosis and evaluate the barriers to treatment for people with that disease or disorder. With assistance from the mentor, by the end of the project, each intern will demonstrate an understanding of diagnostic criteria and current treatment plans for that ailment, the population impacted most commonly by the disease, and will be able to speak about the lived experience of the patients with that disease. This process will develop research skills as well as teach technical reading and writing. This will advance interns’ critical thinking and independent research skills in a supportive, interdisciplinary environment. The interns will leave the program with a better sense of the field of science and medical studies in the humanities.
Required skills for interns prior to acceptance: None
LIT-04: Reconfiguring Displacement and the “American Dream” through Borderland Stories
Primary mentor: Maria Pachon
UCSC faculty contact: Prof. Micah Perks
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Every year, thousands of migrants attempt to cross the U.S.-Mexico border. To understand the challenges, contradictions, and complexities of what happens at the border, it is important to access migrants’ experiences. The purpose of this research project is to explore the potential of storytelling to capture the complexity of borderland experiences, question fixed national identities, subvert stereotypes, and portray the heterogeneity of the Latinx community. What are the narrative strategies and media that border communities are using to tell their stories? How does their experience of dislocation and relocation affect their relationship with language? How can a border writing be defined? What is the link between storytelling, survival, community building, and collective memory? How has the perception of the “American Dream” changed over time? How can personal stories resist the official narrative about migration?
Tasks:
The SIP interns will: (1) read critical literature on migration, border studies, displacement, memory, transnationalism, and appropriation; (2) explore the creative possibilities and limitations of crossing geographical and language borders; (3) collaborate on the archival research of borderland stories; (4) identify common narrative strategies and themes; and (5) write their own creative piece about migration, and come up with strategies to make space and establish a conversation with the immigrant stories they read without appropriating them.
Required skills for interns prior to acceptance: None
URL: https://creativewriting.ucsc.edu/creativecritical/list-page-grad-page.html
LIT-05: Bug Lit! Insects in Literature and Culture
Primary mentor: Shane Baker
UCSC faculty contact: Prof. Carla Freccero
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Perhaps no other nonhuman form of life has captured the human imagination more than the phylum of insecta (by far the largest phyla of the kingdom animalia). Their predation methods, mating rituals, ancientness, and sometimes uncanny appearance astonish and terrify us. Objects of fear and loathing but also wonder and delight, they have operated for thousands of years as suppliers of symbolic meaning, as ubiquitous on the Earth’s dry surfaces as they are in myth, folklore, literature, and film. We have a love-hate relationship with them: They remind of us death, but also regeneration; they plague and pollinate our crops; they eat us and we eat them. Utilizing some of the research methods of anthropology in addition to literary theory, this research project emphasizes literature — the poem, the short story, the fable, and literary naturalistic description — as a lens through which to view the history of cultural reflection on us and them, the human and the insect. Participation in the research project acts as an introduction to the work of cultural entomology, which is the study of how insects have shaped human societies through the analysis of their representation in cultural artifacts. The SIP interns will also learn the basics of biological taxonomy.
Tasks:
The SIP interns will: (1) search for and aggregate the appearance of various insects in literature and media; (2) be led on a tour through the UCSC Campus Natural Reserve, where they will observe, identify, and document insects in the wild; and (3) read some selections from literary texts that depict insect life and discuss their possible meanings.
Required skills for interns prior to acceptance: None
Microbiology and Environmental Toxicology
MET-01: Microbial Induced Corrosion
Primary mentor: Mitchell Rocereto
UCSC faculty contact: Prof. Chad Saltikov
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Engineered surfaces such as metal and concrete piping are susceptible to microbial influenced corrosion resulting in massive economic losses and increased threats to human and environmental health. Leaky gas and oil pipelines and failures are often attributed to uncontrolled growth of microbes that accelerate metal corrosion. This research project will address the microbial influenced corrosion (MIC) problem by taking a “green” approach to combating microbes known to cause corrosion. The approach will be to isolate and characterize microbial biofilms that inhibit and protect metal surfaces from microbes known to cause corrosion through a process known as MIC. The specific aims of this research project are to: (1) develop an electro-chemical screening platform for quantifying anti-MIC properties of microbial biofilms cultured from diverse environmental sources; and (2) characterize the mechanisms for anti-MIC activities using microscopy, metabolomics, and genomics.
Tasks:
The SIP interns will help collect and screen environmental samples for anti-corrosion biofilm forming microbes. Microbiological techniques will be used to grow and propagate these microbes for further MIC testing. Interns will also learn anaerobic technique and how to use anaerobic bacterial equipment. Interns will also learn data analysis and how to sort genomic data and reference databases to determine taxonomy. Interns will also get experience with R studio and Python in data analysis. Interns will also learn more about microbial induced corrosion and how it affects certain materials. Learning how to read scientific papers as well as breaking them down will also be looked at.
Required skills for interns prior to acceptance: Lab work
URL: https://sites.google.com/ucsc.edu/ucsc-saltikov-lab/
MET-02: Toxin-Antitoxins and Their Molecular Targets’ Co-Evolution
Primary mentor: Caison Warner
UCSC faculty contact: Prof. Manel Camps
Location: 100% remote and online
Number of interns: 3
Project description:
Toxin-antitoxin systems are unique systems found across prokaryotic organisms. These systems are associated with antibiotic resistance, virulence and persistence. We aim to find if there is an evolutionary co-selection pressure between the toxin and its targets. The implication would change the way these systems are understood and classified.
Tasks:
The SIP interns can expect to generate the following:
—Multiple sequences alignments (MSA);
—Protein and host phylogenetic trees;
—Various graphs and heat maps; and
—Literature search and protein homology search.
The interns must have either a Mac or a Windows laptop with Linux installed on it.
Required skills for interns prior to acceptance: Computer programming, statistical data analysis
Molecular, Cell, and Developmental Biology
MCD-01: Elucidating the Genetic Basis of Antibiotic Resistance in Fluoroquinolones
Primary mentor: Amanda Carbajal
UCSC faculty contact: Prof. Manel Camps
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Bacteria are evolutionarily old microbes that have developed a myriad of unique and poorly understood genetic manipulations to achieve survival and evolution whether it’s in a human host or in the environment. They threaten human health in the sense of their success of antibiotic resistance, caused by selection of random mutations within their genome. Two aspects of bacterial biology include the unique mobile genetic element of a plasmid, an independent genetic tool that can be passed on and used “as needed” through horizontal gene transfer, yet little is known specifically about how plasmids help bacteria. This project is driven by the goal to understand how plasmid biology specifically allows E.Coli to be so successful, so that new target therapies may be developed to target and minimize the superbug phenomena.
Tasks:
The SIP interns’ primary task will be to develop a helpful in-house database of the known data on plasmids and biofilm formation mechanisms of action with respect to each species of bacteria. This database will be used to track genetic and mechanistic comparisons among the different strains and how they utilize plasmids. The interns’ secondary tasks will include learning what it means to be a scientist from reading peer-reviewed scientific journals, identifying strong and weak studies, and methods used in the field to achieve the proving of a hypothesis. The interns will learn to network, collaborate, communicate and see a project through. The interns will learn about a field that is emerging that few, if any other labs, are working on.
Required skills for interns prior to acceptance: None
MCD-02: Homeostatic Sleep Mechanisms
Primary mentor: Stefan Abreo
UCSC faculty contact: Prof. Yi Zuo
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Sleep, which is dictated by circadian and homeostatic mechanisms, is impaired in 50 to 70 million adults in the US and, when impaired, has been shown to severely increase the risk of mental and physiological maladies like depression, anxiety, diabetes, and cardiovascular disease. Homeostatic sleep processes, the regulatory mechanisms that compensate for extended periods of wakefulness, are greatly understudied. My project will show that waking-associated increases in neuronal DNA damage increase the pressure towards sleep, and identify new molecular targets for therapeutics.
Tasks:
The SIP interns will gain experience in PCR genotyping, stereotactic surgery, murine behavioral protocols and analysis, intracardiac perfusions, neural tissue preparation, immunofluorescence, confocal microscopy, and data consolidation. The interns are expected to be meticulous note-takers, have good time management skills, and have the motivation to review scientific literature and ask as many questions as they can!
Required skills for interns prior to acceptance: None
MCD-03: Neuronal Population Encoding
Primary mentor: Brian Mullen
UCSC faculty contact: Prof. David Feldheim
Location: In person/hybrid on the UCSC campus
Number of interns: 3 + TSIP
Project description:
The Feldheim lab is interested in the superior colliculus (SC), a structure in the midbrain where visual, auditory, and somatosensory information are integrated to initiate motor commands. Sensory integration is key to perceiving and responding to our environment, however each individual neuron lacks consistency between individual trials to give a complete understanding of the environment. The population of neurons, i.e. circuit, will better inform the organism of its perceptions. As such, our lab has performed electrophysiogical recordings of neurons on awake mice while recording from the SC, while presenting various visual and auditory stimuli.
Tasks:
When the researchers place the electrodes into the brain, they do so blindly. After the experiment, they dissect out the brain and stain the tissue to reveal the location of the probes. To understand the data fully, the research group need tools to align the location of the electrodes to an established mouse atlas. This will assist in the research group’s interpretations of the data. This summer, the SIP mentors and SIP/TSIP interns will be building a graphic user interface (GUI) in Python to align the electrophysiological probe placement to a known mouse atlas.
Required skills for interns prior to acceptance: Computer programming, lab work, statistical data analysis
Music
MUS-01: Music, Experimental Video, and Storytelling
Primary mentor: Nina Barzegar
UCSC faculty contact: Prof. Ben Leeds Carson
Location: 100% remote and online
Number of interns: 4
Project description:
The focus of this research project is on exploring the relationship between music, motion picture, and personal storytelling. The mentorship aims to deepen the interns’ understanding of this concept and empower them to create impactful sonic designs for experimental video productions. Throughout the research project, the SIP interns will immerse themselves in the world of experimental storytelling, drawing from their own experiences, cultural backgrounds, emotions, and memories. The interns will analyze the themes, moods, and narratives within their stories to discover how music can enhance and amplify their video experience. By exploring different musical elements, techniques, and instruments, the SIP interns will develop expressive possibilities that align with their personal narratives. Additionally, the research project will cover technical aspects of music and sound design for motion pictures, emphasizing how sonic elements contribute to the overall narrative and audience experience. Collaborative exercises and workshops will enable the interns to experiment with composing and designing soundscapes that enhance the dramatic impact of their explored stories. Ultimately, the research project will culminate in the interns applying their acquired knowledge and analytical skills to create a short video accompanied by a thoughtfully crafted sonic design.
Tasks:
The SIP interns’ tasks will include: (1) learning and research — exploring music, motion picture, and storytelling concepts through research and examples; (2) creative exploration — reflecting on personal experiences to generate ideas and experimenting with storytelling techniques; (3) Logic Pro training — learning the basics of using Logic Pro, a software for music composition and editing; (4) video production — planning and capturing video footage, and creating visual compositions; (5) sound design — applying music and sound to enhance the video’s mood and narrative within Logic Pro; (6) editing and integration — combining video and sound elements in video editing software; and (7) presentation and reflection — sharing their completed video projects and reflecting on the creative process.
Required skills for interns prior to acceptance: None
Ocean Sciences
OCS-01: Detection and Attribution of Chlorophyll Trends in the North Pacific
Primary mentor: Dongran Zhai
UCSC faculty contact: Prof. Claudie Beaulieu
Location: 100% remote and online
Number of interns: 3
Project description:
Global climate change increasingly affects marine ecosystems, altering their physical, chemical, and biological environment. Based on coupled model projections, a global decline in primary productivity is expected due to changes in temperature, light, nutrients, and grazing. A decrease in primary productivity has the potential to reduce CO2 uptake by the gyres, with ramifications for the global carbon cycle. The concentration of chlorophyll-a is an important proxy for ocean primary production. This project is mainly about statistically detecting a change in the North Pacific subtropical gyre in satellite chlorophyll and determining the underlying cause(s). We will analyze satellite chlorophyll over 1998-2022 in the North Pacific subtropical gyre to quantify recent change and uncertainty.
Tasks:
The SIP mentor and interns will characterize the signal of observed change and test whether the signal detected is larger than the natural variability of chlorophyll observed in the region. Then, the research group will retrieve coupled model simulations of chlorophyll over that region and perform an attribution of the observed decline. As such, the reearch group will determine the expected signal of change in chlorophyll with and without anthropogenic forcing and quantify its contribution to the change detected in observations. This work will be conducted using the R computing software. The interns will: (1) learn the skills of data analysis and visualization; (2) gain experience about deal with satellite data and coupled model simulations; and (3) master R computing software.
Required skills for interns prior to acceptance: None
Physics
PHY-01: Study of Two-Dimensional Semiconductor Devices
Primary mentor: Carlos Gonzalez
UCSC faculty contacts: Prof. Jairo Velasco, Jr., Prof. Aiming Yan
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Recent experimental studies of two-dimensional (2D) materials, otherwise known as van der Waals heterostructures, have shown promising results for the creation of new devices that exhibit exciting electronic, magnetic, and optical properties. One such group is the transition metal dichalcogenide (TMD) family which can manifest as either conducting or semiconducting. Semiconducting TMDs show promise to replace silicon as the semiconductor in electronic devices, allowing for smaller and more flexible electronics. In this project, we will be fabricating stacks of 2D materials to further study the properties of TMDs through various methods.
Tasks:
In this research project, the SIP interns will get the opportunity to get hands-on experience in a research lab. They will learn fabrication of 2D materials, such as scotch-tape exfoliation and material synthesis. These materials will then be characterized through different methods to observe their physical properties, observing first-hand the miniscule size of the materials that are studied. Finally, these materials will be fabricated into devices to observe the electronic properties exhibited. Research into assigned papers on 2D materials will assist the understanding of the methods and observations in the lab.
Required skills for interns prior to acceptance: None
URL: https://jvjlab.sites.ucsc.edu/
PHY-02: Transfer Matrix Modeling Optical Properties of Short-Period Aluminum Oxide-Copper Multi-Layered Nanocomposites
Primary mentor: Soren Tornoe
UCSC faculty contact: Prof. Nobby Kobayashi
Location: 100% remote and online
Number of interns: 3
Project description:
Semiconductors are the heart of modern-day computers, and Moore’s law is starting to break down (i.e., transistor density is no longer doubling every two years). As such, new approaches and materials are needed for the next generation of semiconductors to keep the technology advancing as rapidly as it has in the past. Through the use of sputtering atomic layer augmented deposition (SALAD) – the combination of physical vapor deposition (PVD) and chemical vapor deposition (CVD) techniques used to make thin films – aluminum oxide-copper mirrors were produced that showed optical properties similar to semiconductors; however, these unique optical properties cannot be well described by conventional methods. The goal of this research project is to model these optical properties and therefore understand the unique physics that has been presented.
Tasks:
The SIP interns will model and optimize the optical properties of short-period aluminum oxide-copper multi-layered nanocomposite mirrors by writing code using a programming language like MATLAB/GNU Octave and developing transfer matrices to calculate the reflective properties of the coated mirror. The mentor will teach a basic understanding of light interactions on multilayered thin film structures as well as go over the principles behind creating transfer matrices and why they are an optimal means of calculation for multilayered optics. Computer programming experience is strongly recommended but not required.
Required skills for interns prior to acceptance: None, computer programming experience strongly recommended
PHY-03: Study of Defect-Induced Magnetism in Few-Layer MoS2
Primary mentor: Hem Prasad Bhusal
UCSC faculty contact: Prof. Aiming Yan
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Inducing magnetism in non-magnetic two-dimensional (2D) materials provides a unique opportunity to realize magnetism in the 2D limit. Previous studies have shown that defects in some transition metal dichalcogenide (TMD) materials can exhibit promising 2D magnetism. In this research project, the SIP mentor and interns will create triangular defects (antidots) in a few-layer molybdenum disulfide (MoS2), one of the most popular semiconductors TMD materials. After that, the group will characterize the defects using atomic force microscopy (AFM) and fabricate field-effect transistor (FET) devices out of MoS2 having antidots. Finally, the group will measure the sample in the cryostat to study 2D magnetism. This study promises to provide an experimental way of exhibiting 2D magnetism in non-magnetic 2D materials.
Tasks:
This research project mainly involves experimental work in the lab. The first step in the experiment is to prepare the sample for the transmission electron microscopy (TEM) study. The SIP interns’ help during sample preparation is crucial. For this project, the interns will perform the mechanical exfoliation (using scotch tape) of bulk chromium trihalides and bulk graphites to get few-layer flakes. In the next step, the interns will use the optical microscope to characterize the thickness and size of the obtained flakes. Furthermore, the interns will learn and help in Atomic Force Microscope (AFM) characterization to estimate the layer numbers of the flakes. Finally, the interns will learn how to transfer flakes to make heterostructures and then stamp down the heterostructure onto a TEM substrate. Then, the sample will be ready for TEM study for structural characterization.
Required skills for interns prior to acceptance: None
Psychology
PSY-01: Perceptual Strategies and Emotion Recognition in Individuals With Different Levels of Autistic Traits
Primary mentor: Golnoosh Soroor
UCSC faculty contact: Prof. Nicolas Davidenko
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
The mentor’s research group is using eye tracker and Matlab to test if they can change the strategies of face perception and see if it can help to improve emotion recognition. The research group wants to know if these strategies are different in individuals with autistic traits, using eye-tracker, and if the group can help individuals improve their skills in emotion understanding. In the next research project, the mentor’s research group will probably work with children with autism to find out about the development of face perceptual strategies and see if the research group can improve face and emotion recognition in clinical population.
Tasks:
Required skills for interns prior to acceptance: None
URL: https://psychology.ucsc.edu/about/people/grad-directory.php?uid=gsoroor
PSY-02: The Masculinity Socialization of Young Men Participating in High School Football
Primary mentor: Miguel Lopezzi
UCSC faculty contact: Prof. Regina Langhout
Location: In person/hybrid on the UCSC campus
Number of interns: 4
Project description:
Masculinity socialization refers to the social process men experience while learning the gender roles and norms that are expected of them in social interactions and cultural environments. High school football programs provide a social environment for young men to learn the gender norms and roles expected of them to be masculine and become men. This type of socialization process often includes being strong, tough, and stoic. In this research project, we will work together to understand the masculinity socialization of young men participating in a high school varsity football team. We will explore how these young men are internalizing masculinity and what being a “man” means to them.
Tasks:
The SIP interns will read and get familiar with research topics related to masculinity socialization. The SIP interns will learn about qualitative research methods by working on a thematic analysis. SIP interns will also learn about how ethnographies are conducted and how data is collected through observations and fieldnotes. SIP interns will work with data collected (fieldnotes) from an ethnography of high school students who participated in a varsity football team. The interns will be working on an actual qualitative research study. No experience is necessary as interns will learn all these skills in this summer’s SIP program.
Required skills for interns prior to acceptance: None
PSY-03: Mapping Racism: Exploring Engagement with Critical Racialized Place Based Education
Primary mentor: Jada Cheek
UCSC faculty contact: Prof. Courtney Bonam
Location: 100% remote and online
Number of interns: 3
Project description:
This project will focus on race and social justice; specifically how racial stereotypes not only apply to people but also physical places. These space-related racial biases can influence the environments around marginalized spaces and affect what resources are allocated to certain neighborhoods, profiling a physical space as lesser than when occupied by Black people vs. White people. The stereotypes and profiling can have a detrimental effect on the lives of the people that occupy these spaces and maintain racial inequity.
Tasks:
The SIP interns’ tasks will consist of reading background literature surrounding the psychological phenomena of racialized physical spaces, critical race theory, and racial stereotypes. The interns will also help to code data and potentially help run and analyze statistical tests.
Required skills for interns prior to acceptance: None
URL: https://sites.google.com/ucsc.edu/race/home
PSY-04: Brain Activity Underlying Visual Perception and Decisions
Primary mentor: Audrey Morrow
UCSC faculty contact: Prof. Jason Samaha
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
This project uses cognitive neuroscience approaches to analyze brain activity associated with visual perception. Specifically, this mentor looks at electroencephalography (EEG) data, which is a record of electrical activity from cortical parts of the brain, to assess brain waves and event-related changes in brain potential (ERPs) from brain areas associated with vision. Alpha power and sensory-related responses in the brain change during visual attention. These changes are associated with changes in task performance as well as later brain activity related to confidence and decision-making.
Tasks:
The SIP interns on this research project will gain an understanding of how EEG data are analyzed and what those analyses can tell us about patterns of brain activity when we attend to and make decisions about visual information.
Required skills for interns prior to acceptance: None; computer programming experience recommended
URL: https://samahalab.ucsc.edu/
PSY-05: Enacting Change: Learning from Activist’s Transformative Change Visions, Processes, and Actions
Primary mentor: Daniel Rodriguez
UCSC faculty contact: Prof. Regina Langhout
Location: 100% remote and online
Number of interns: 3
Project description:
If you identify as an activist or are interested in the psychology of activism, you’re a good fit for my research team. Activists are working together to change the world. Transformative change means addressing a problem at its core, in other words, ‘changing the rules of the game.’ We’ll learn from activists how they collaborate to enact change in their organizing spaces and the communities they want to serve. In other words, we’ll learn how activists envision and enact change toward co-creating utopian futures of ideal co-existence.
Tasks:
This qualitative research psychology study will allow the SIP interns to transcribe and analyze interviews with impactful activists. The interns will learn to read, make short summaries, and discuss academic articles on the psychology of activism and transformative change. They will learn the basics of qualitative research to then use these skills in transcribing and conducting early analysis of activists’ social change efforts. Previous experience in research is optional, as interns will learn qualitative research skills in my team. What is necessary is that the interns are passionate about activism. The research results will amplify activists’ social transformation efforts to inspire teaching and scholar-activism on co-creating more equitable ways to reorganize society.
Required skills for interns prior to acceptance: None
URL: https://cprat.sites.ucsc.edu/graduate-students/
PSY-06: Moral Psychology in Everyday Experiences Surrounding Honesty and Cheating
Primary mentor: Mia Kottgen
Secondary mentor: Dr. Talia Waltzer
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: In person/hybrid on the UCSC campus
Number of interns: 4
Project description:
Why do so many students cheat in high school? Many contextual factors (e.g., teachers, peers) can shape adolescents’ and emerging adults’ beliefs and everyday ethical decision-making. This study will examine students’ experiences from their classes and judgments about hypothetical vignettes involving cheating. Interns would work on literature review, study design, recruiting high schools for the study, and piloting the project. This project fills a need for more naturalistic research on moral decision-making and will advance knowledge about how social messaging informs students’ evaluations of academic cheating.
Tasks:
To learn more about moral decision-making and academic integrity, the SIP interns will assist with data organization and analysis. By the time of summer, the research project will have completed data collection, so one goal for this summer is to analyze the data and apply coding schemes to the data. The intern’s tasks will involve reading published research papers, designing and piloting study procedures, and analyzing data about students’ attitudes and experiences. Past interns have also learned about how to analyze data using the programming language, R. The schedule will involve independent work on the project, daily check-ins with the mentor, group activities, and weekly team meetings to discuss project progress.
Required skills for interns prior to acceptance: None
PSY-07: Naive Biology: Do Children Think Robots Have Biological Insides?
Primary mentor: Elizabeth Goldman
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: 100% remote and online
Number of interns: 3
Project description:
Robots are becoming a major part of our society. This research project aims to investigate how young children perceive robots. This is an important topic because many robots are being designed and marketed for children. However, we do not understand how these robots impact children and their development. Specifically, we are investigating whether young children understand robots are mechanical and do not have the same biology as humans. In this research project, children will play a sorting game with the researcher. Children will be shown pictures of different robots, animals, and objects. The children will then be asked to identify whether something biological (e.g., bones) or mechanical (e.g., gears) goes inside the item in question.
Tasks:
The SIP interns will observe the children’s reactions and take detailed notes. This research project has already been designed and the mentor is testing out the procedure with young children (e.g., making sure the young children can understand the directions and complete the study). This project is being run in two formats: Zoom sessions with children and via a survey that parents administer to their child. Come learn about online research studies and the multiple ways we can collect online data. This summer, the mentor’s research team will work together to collect as much data as possible. The SIP interns and the mentor’s research group will then work together analyze the data they have collected. This research project could impact how robot designers create and build robots for young children. Join the mentor’s research team and discover how young children perceive robots!
Required skills for interns prior to acceptance: None
URL: https://eljgoldm.wixsite.com/my-site
PSY-08: Neural Mechanisms of Perceptual Decision Making
Primary mentor: Wei Dou
UCSC faculty contact: Prof. Jason Samaha
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
We frequently need to make timely decisions based on sensory information we perceive from the external environment. And the subjective judgment about our own perceptual processing is a fundamental feature of adaptive behaviors. This project focuses on investigating the neural mechanisms of perceptual decision making and the subjective confidence of the decision using the electroencephalogram (EEG). The results could shed light on how perceptual decision making and its confidence are supported or implemented by the electrical activity produced by populations of neurons.
Tasks:
The SIP interns will do background reading about perception, research methods in psychology, neuroscience, and EEG technique. They will gain experience with basic MATLAB programming, and EEG data preprocessing and analysis using MATLAB. The interns will also learn how to conduct literature reviews on relevant topics, design an experiment, and present research papers.
Required skills for interns prior to acceptance: Computer programming, statistical data analysis
PSY-09: Misinformation on Social Media
Primary mentor: Karinna Nazario
UCSC faculty contact: Prof. Adriana Manago
Location: 100% remote and online
Number of interns: 4
Project description:
Social media has played a big role in the spread of information, both true and misinformation. This research project will examine the spread of misinformation on social media. Interns will conduct a literature review on the spread of misninformation and then apply the latest research to their own observations of how information is spread on Twitter and TikTok. Interns will create different accounts– one following conservative politicians and activists, and one following liberal politicians and activists so that they can compare how information is spread in these two subcultures online. Interns will then conduct a content analysis of comments and debates in the posts, and use a thematic analysis to look for themes in posts, comments, and debates.
Tasks:
Interns will be conducting a literature review on misinformation, review how to conduct a thematic analysis, go on social media accounts to monitor the spread of information and misinformation, create themes based on the content they view on social media, categorize the content, and present the findings for the final SIP presentation.
Required skills for interns prior to acceptance: None
PSY-10: Earworms
Primary mentor: Matt Evans
UCSC faculty contact: Prof. Nicolas Davidenko
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
Have you ever had a song get stuck in your head? Probably! Nearly everybody regularly experiences “earworms,” but very little is known about how and why they happen. The scientific literature refers to earworms as Involuntary Musical Imagery (INMI), and empirical research on the phenomenon is quite limited. The SIP interns will help contribute to the scientific understanding of various aspects of this near-ubiquitous human experience.
Tasks:
The SIP interns will conduct detailed literature review and analysis of existing work on Involuntary Musical Imagery, Voluntary vs. Involuntary Memories, and Mind-Wandering. Each intern will present on at least one article during a research group meeting over the course of the summer, leading a deep-dive discussion. Throughout the summer, the interns will also be the primary researchers responsible for running human participants through an in-lab study on the effects of cognitive load on involuntary musical imagery duration. As data are collected, the SIP interns will clean and screen data to prepare it for statistical analysis.
Required skills for interns prior to acceptance: None
PSY-11: White Emotionality as a Tool for (Dis)Engagement in Classroom Settings: Student Experiences in Community Psychology Courses
Primary mentor: Alix Macdonald
UCSC faculty contacts: Prof. Gina Langhout, Prof. Courtney Bonam
Location: 100% remote and online
Number of interns: 3
Project description:
Research in critical whiteness studies states that the expression of emotions (i.e., anger, defensiveness, guilt, and shame) in certain contexts is not always neutral. Rather, the expression of certain emotions from those in positions of privilege may operate to uphold the status quo and dominant power structures; in this case, we are focused on white supremacy in educational settings. This research project looks at two research questions: (1) How are students experiencing this Community Psychology course in different destabilizing contexts?; and (2) What emotions are students choosing to write about in their course evaluations, and how does that relate to their acceptance or resistance of the course framework? Using student experience of teaching surveys (SETS) and lecture transcripts, we are conducting reflexive thematic analysis to discern how students are accommodating and/or resisting the course framework in their SETS. In this project’s context, the Community Psychology course is taught from an anti-racist and trauma-informed, and reflexive framework that works to disrupt current dominant narratives.
Tasks:
The SIP interns will read and get familiar with research topics related to critical whiteness studies. The interns will learn about qualitative research methods by working on reflexive thematic analysis coding. The SIP interns will be working on an actual qualitative research study. No experience is necessary as the interns will learn all these skills in the course of this summer’s SIP research project.
Required skills for interns prior to acceptance: None
PSY-12: Media Silence and Underreporting with Prisons
Primary mentor: Jade Moore
UCSC faculty contact: Prof. Craig Haney
Location: 100% remote and online
Number of interns: 3
Project description:
In this research project, the SIP interns will investigate how correctional officers’ abuse and how the dynamics within prisons are portrayed in the media. The interns will analyze different media outlet reports (newspapers, broadcasts, etc.) to investigate how forms of moral disengagement may translate over in correctional institutions. The interns will also explore other themes that may present themselves. The goals of the research project are to establish the types of narratives that the media is portraying and what kind of information the media has access to when investigating reports of abuse within prison.
Tasks:
The SIP interns will read and have discussions on a range of scientific articles focused on the idea of discrimination in the criminal justice system that will contribute to the literature review for the study. The interns will also assist with finding media outlet reports on the topic of correctional officers’ abuse of power. Interns will then work on coding the reports and running a statistical analysis of the findings. Interns can expect to gain insight into the process of developing a literature review, coding newspapers and news broadcasts, and running and analyzing statistical analyses.
Required skills for interns prior to acceptance: None
PSY-13: Neural Activity During Online Language Comprehension
Primary mentor: Yaqi Xu
UCSC faculty contact: Prof. Megan Boudewyn
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
In this research project, the SIP interns will work with electrophysiological data collected from the Cognitive Neuroscience Lab led by Dr. Megan Boudewyn at UC Santa Cruz. The data will be electroencephalography (EEG) data, which is a cognitive neuroscience method that involves recording electrical activity from cortical parts of the brain via electrodes placed on the surface of the scalp. The experimenters are primarily interested in analyzing the time-locked event-related potentials (ERPs) and wave oscillations associated with online language comprehension to get a better understanding of how our brain processes language. The interns will learn how to look at and analyze EEG data, the neural patterns that are associated with language comprehension, and the relationship between different cognitive functions such as attention and executive control and language processing.
Tasks:
The tasks assigned to the SIP interns may include a combination of the following: (1) shadow experimenters during actual experiments with human subjects; (2) monitor electrophysiological signals while subjects are in the testing rooms; (3) managing and cleaning supplies used in experiments (which may include electrodes, applicators, and caps used in the experiments); (4) build stimuli sets and help create future experiments; (5) help code current stimuli sets and prepare data for analysis; and (6) search databases for past related research and compile and summarize their methods and results.
Required skills for interns prior to acceptance: None
PSY-14: Language and Cognitive Processes Studies
Primary mentor: Nathan Caines
UCSC faculty contact: Prof. Megan Boudewyn
Location: In person/hybrid on the UCSC campus
Number of interns: 3
Project description:
This research project in the Cognitive Neuroscience Lab run by Prof. Megan Boudewyn, involves potentially working with electrophysiological (EEG) data as well brain stimulation techniques (tDCS) to study cognitive processes surrounding language. The mentor’s research group is interested primarily in oscillatory brain signals as well as event related potentials associated with language comprehension. The SIP interns will have the opportunity to learn both theoretical and practical implications of cognitive neuroscience research at different stages.
Tasks:
The SIP interns on this research project will work on the following tasks: (1) stimuli creation; (2) data collection; (3) data processing; (4) literature review; and (5) shadowing experiments and monitoring data.
Required skills for interns prior to acceptance: None
URL: https://sites.google.com/ucsc.edu/boudewynlab?pli=1
PSY-15: Understanding Voice Assistant Communication
Primary mentor: Elise Duffau
UCSC faculty contact: Prof. Jean E. Fox Tree
Location: 100% remote and online
Number of interns: 3
Project description:
The SIP mentor is interested in expanding on how we communicate with artificial agents. To explore this, research is being done on two research projects. The first research project aims to understand how people respond to voice assistants’ use of politeness. The second research project aims to understand how people respond to misunderstandings and addressing misunderstandings by a voice assistant. The SIP interns will gain an understanding of how communication between people and voice assistants can be different as well as ways that we can improve communication with voice assistant technology.
Tasks:
The SIP interns will gain experience in the various aspects of psychological experiments. The interns will work with the mentor in learning how to conduct research in cognitive psychology related to communication with technology. This will include engaging in: experimental design, conducting literature reviews, working with data and coding, and transcribing audio data. The SIP interns will also gain experience in understanding and discussing relevant literature as well as how to effectively communicate research to a wide audience.
Required skills for interns prior to acceptance: None
Sociology
SOC-01: Trans Poetics in the Transsexual News Telegraph Archive
Primary mentor: Kaiya Gordon
UCSC faculty contact: Prof. Marcia Ochoa
Location: 100% remote and online
Number of interns: 3
Project description:
Since the development of Compton’s Transgender Cultural District in 2017, there’s been a spotlight on San Francisco’s trans lineage. At the same time as this attention, and not unrelated to it, recent moves by Mayor London Breed to increase surveillance and police presence in the Transgender District/Tenderloin points to an overwhelming culture of violence against trans people in the city. When trans people divorce ourselves from the past, we lose a long line of resistance and solidarity actions––things which can be brought into the future as strategies for liberation. The mentor’s project––a creative consideration of the Transsexual News Telegraph collection at the GLBT Historical Society and Archives in San Francisco––addresses these strategies by working with and responding to this important trans collection.
TNT, published between 1991 and 2002 in San Francisco by editor Gail Sondegaard (pseudonym), was a quarterly magazine which published trans-related news, essays, reviews, photographs, art, and events. As a DIY magazine which featured non-institutionally affiliated community members, TNT can be located as an early branch of the study of trans people by trans people, outside of academic, legal or medical institutions. The TNT collection includes notes on important moments in trans history, including the Michigan Womyn’s Music Festival and Camp Trans, the development of transgender-related internet sites, and local protests.
By joining this project, SIP interns will both learn concrete Archival Science methods, and respond to the inaccessibility of trans history. Interns will build data processing, transcription, research, and critical thinking skills, and will be introduced to trans-specific issues, narratives, and debates.
Tasks:
The SIP interns’ specific tasks will include transcription of the TNT archival collection, as well as data processing, coding, description, analysis, and creative response. The interns will be asked to locate and describe narratives and themes within the collection. The interns will be subsequently asked to choose data within the collection, and to prepare research presentations and a creative response in response to that data. Should any interns be able to travel to San Francisco, there will be the opportunity to visit the GLBTHS reading room and meet the archivist in person. Regardless, regular meetings with the mentor will include drop-ins by archivists and the faculty mentor.
Required skills for interns prior to acceptance: None
SOC-02: Mobilities (Migration and Higher Education), Gender, and Sexuality
Primary mentor: Michelle Parra
UCSC faculty contact: Prof. Julie Bettie
Location: 100% remote and online
Number of interns: 4
Project description:
How does pursuing mobility via migration and higher education shape US Latinas’ own gender and sexual identities as well as generational negotiations of gender and sexuality? Previous research finds that both migrating and attending college can shape people’s gender and sexual beliefs and behaviors. Scholars also note that undergoing a substantial mobility experience, such as migrating, can shape how Latinas employ generational negotiations of gender and sexuality. Less is known about how another mobility path, going to college, shapes the generational negotiations Latinas employ of these social forces. Hence, this project utilizes sociology, feminist studies, ethnic studies, and queer theory to examine how Latinas’ migratory and college-going experiences shape their own gender and sexualities and generational negotiations of these social forces within the family.
Tasks:
The SIP interns will have an opportunity to read literature on gender, sexuality, migration, and education. They will learn how to retrieve scholarly journals and write critical research summaries (annotations). In addition, interns will assist the mentor with transcribing and reviewing (coding) qualitative data. In doing so, they will also learn how to analyze qualitative data. Interns will also have the opportunity to create a research presentation based on the literature that they read and the interviews that they coded. Lastly, the mentor will invite the interns to present their research findings in an undergraduate Sociology course that the mentor is teaching this summer.
Required skills for interns prior to acceptance: None
URL: https://sociology.ucsc.edu/about/directory-grads.php?uid=mparra3
SOC-03: Legacies of Black and Indigenous Sovereignty in the African Diaspora
Primary mentor: Theresa Hice-Fromille
UCSC faculty contact: Prof. Rebecca London
Location: 100% remote and online
Number of interns: 3
Project description:
Marronage is a practice of freedom, a fugitive state, and place-making endeavor (Roberts 2015; Wright 2020; Winston 2021). Fugitive slaves, free people of color, Indigenous peoples, and occasionally white colonials collaboratively built maroon communities, also known as palenques (Spanish) or quilombos (Portuguese), in difficult, mountainous, and swampy environments in the Americas and Caribbean to shield them from the persistent violence of the plantation. Scholars have used marronage as a metaphor to understand contemporary fugitive practices but this research project will focus on historic and existing maroon communities in Cuba, Costa Rica, and Colombia. The SIP interns will examine de-identified primary data including ethnographic field notes and interviews with Black travelers who visited these sites between 2019 and 2023. The interns will contemplate the convergences and divergences in the meaning of sovereignty during enslavement and within contemporary calls for abolition and anti-racism, and challenges to the global racial capitalist order. This research primarily draws on concepts from African diaspora studies, decolonial studies, politics, sociology, and human geography.
Tasks:
The SIP interns’ tasks will include:
(1) Literature— The interns will be introduced to foundational themes in decolonial and Black geographies literatures. The interns will learn how to locate, annotate, and summarize academic articles. The interns will develop a literature review and learn the significance of the literature review for the research process.
(2) Qualitative Data Analysis— The interns will learn how to create memos and code qualitative data.
(3) Presentation— The interns will present their literature review, code book, and preliminary analysis at SIP’s Presentation Day. Other opportunities to present during UCSC summer instruction may also be available.
Required skills for interns prior to acceptance: None