2021 Research Projects (Old)

We will continue to post projects to this page as they are approved. Please check back periodically for updates.

Note:
Each research project will involve background reading for the interns provided by their mentors.
Each research project will involve a final presentation by the interns.

Interns are expected to work collaboratively on the same project and/or data set.
This may preclude rising seniors from submitting papers based on such projects to the Regeneron Science Talent Search competition

Please feel welcome to research the projects and labs associated with the SIP Research Projects listed below, but PLEASE DO NOT contact any mentors or faculty. Mentors will reach out to admitted interns who have been assigned to their projects during the research preparation weeks of June 7–18, 2021.

Anthropology 

Project code: ANT-01
Title: Technology and Oral Story Collection of Indian Immigrants in the USA
Primary mentor: Kati Greaney
Faculty advisor: Dr. Annapurna Pandey
Location: Remote/online
Number of interns: 4

Project description:
These days, one often hears that we human beings are primarily story tellers. We tell stories about ourselves as well as about others. What these stories tell us is the rich experience human beings have acquired in their life. The world in which we live today is largely created by technology. The mentor and SIP interns will use various tools provided by technology in their digital story telling research. This project will encourage SIP interns to collect stories about the immigrant experience in the United States. For the last three decades the mentor has been working on the Indian diaspora in the Greater Bay Area, California. The mentor has made two films, “Homeland in the Heart” and “Life Giving Ceremony of Jagannath” documenting the involvement of Odia people (people from the state of Odisha) in building a community and developing a sense of belonging to the United States. The mentor would like to broaden the scope of this research by incorporating the experiences of other Indian immigrants.

Tasks:
This project will give an opportunity to the SIP interns to collect oral history material about the experiences of immigrant parents, grandparents, and their American-born children. The material will include streaming audio and written transcripts accessible online in digital formats. The mentor and SIP interns will use various available technology tools. The mentor’s aim in this project is to collect interviews of Indian immigrants in the USA. The SIP interns will interview various members of the Indian community and collect their experiences in this country compared to their experience in their homeland that they have left behind. These interviews are a unique source of contemporary history through the experiences of the immigrants. Past studies have shown that this kind of research has revealing consequences for both the researchers as well as the subjects of their research. Students who have experience and interest in film making, video-making technology, and video editing are encouraged to apply.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

Applied Artificial Intelligence 

 

Project code: AAI-02 (CSE)
Title: Procedural Road Generation for Self-Driving Vehicles
Primary mentor: Golam Md. Muktadir
Faculty advisor: Prof. Luca de Alfaro
Location: Remote/online
Number of interns: 4

Project description:
In this project, we build algorithms which can automatically generate roads in digital format which can be used in simulation or game engines such as Unity or Unreal Engines. This procedural generation reduces the amount of human effort in designing digital roads. Our goal is to make novel algorithms that can generate roads which are similar to real-world roads. Current work generates roads which either requires a lot of real-world data and human effort, or generates a very limited set of variations. Anything produced by interns in this project is publishable as papers. Interns will learn about self-driving car development, how their simulation is done, and how to code for them! We can even use AI to simulate driving with the roads that will be created!

Tasks:
Interns will (1) learn about self-driving car research and development; (2) learn to do Python programming with clean code (extremely valuable); (3) solve geometric problems with coding; and (4) run simulations (optional).

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming

URL: https://github.com/AugmentedDesignLab/junction-art

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AAI-03 (ELE)
Title: Energy Data Analytics
Primary mentor: Jing Xiong
Faculty advisor: Prof. Yu Zhang
Location: Remote/online
Number of interns: 3

Project description:
Have you heard of the Smart Grid on the news or from your energy provider? In this next generation of the electric grid, a huge amount of data is generated and exchanged every day: markets, equipments, and power system data which can be used for reliable and efficient planning and operation, predicting states, providing situational awareness, analyzing stability, detecting faults and providing advance warning. Therefore, energy data analytics have a significant role to make the grid more intelligent, efficient, and productive. This summer, the mentor and SIP interns will explore machine learning (ML) and deep learning (DL) models to play with the energy data, build up the pipeline and increase the performance.

Tasks:
The SIP interns will: (1) learn to use Python for programming; (2) gain experience in machine learning frameworks and/or deep learning frameworks such as pytorch; (3) gain exposure on how to collect data from online resources; (4) gain exposure to multiple ML/DL techniques for time series data analytics; (5) learn how to read related research papers; and (6) work collaboratively as a team.

Special age requirement: Interns must be 16 years old by June 21, 2021.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Art, Culture, & Stem

Project code: ACS-01 (AST)
Title: Native Skywatchers – Starry, Starry Nights Collaboration: We Are Stardust
Primary mentor: Prof. Annette Lee (St. Cloud State U.)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: Remote/online
Number of interns: 8

Project description:
As described by Mi’kmaw elders: “Two-Eyed Seeing is learning to see from one eye with the strengths of Indigenous knowledges and ways of knowing, and from the other eye with the strengths of Western knowledges and ways of knowing, and to use both these eyes for the benefit of all” (Bartlett, Marshall, and Marshall 2012, 336). This collaboration will follow in the spirit and framework of Two-Eyed Seeing, with particular emphasis on the last line ‘use both these eyes for the benefit of all’. It builds on the existing Native Skywatchers research and programming initiative in a unique merger with the Starry, Starry Nights initiative. The goal is to give students a unique opportunity for authentic involvement in science and to weave in cultural relevance equally into the experience to produce the highest level of engagement, excitement, and meaning for all involved. This project lives at the intersection of science, art, and culture.

Tasks:
The SIP interns’ tasks will include the following: (1) participating (remotely) in night time observing with the Lick Observatory in California and Keck Observatory telescope in Hawai’i; (2) digital art (recording, video editing, etc.); (3) Citizen Science; (4) creating art; and (5) documenting and sharing multiple views, ways of knowing, and culture.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work, statistical data analysis

URL: https://nativeskywatchers.com

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ACS-02 (CHE)
Title: Project Coffee Art — Intersection of Art, Chemistry, Racial Harmony, and Social Justice
Primary Mentor: Saul Villegas
Faculty advisors: Sudakshina Ghosh (retd.), Prof. Jennifer Parker
Location: Remote/online
Number of interns: 3

Project description:
Coffee is one of the most enjoyed drinks. In this research project, the SIP interns and mentors are going to investigate the chemistry involved in the journey of the bean from its raw stage to the cup of coffee and explore how coffee grounds can be used to create works of art. The art works created with coffee should reflect racial harmony. The goal of this research project is to give the interns an opportunity to experience the intersection of art, science, and the humanitarian aspects of life. Submission of art works to The Coffee Art Project will allow for active participation in social work. The Coffee Art Project is a high-profile art competition that invites artists to interpret the theme of coffee. Their aim is to support and encourage artists by providing them with a platform to showcase their work and promote coffee culture. Artists at all levels can enter one piece of artwork that connects to ‘coffee’ and/or ‘coffee shop’ experience. The exhibition of art works helps them to raise money to support Project Waterfall which is committed to bringing clean water to communities that grow our coffee through the Allegra Foundation and other registered charities.

Tasks:
The SIP interns will read scientific articles about the chemistry involved in roasting and grinding coffee beans and have a discussion followed by writing short reports. The interns will also study a painting done with coffee and write a brief description based on group discussion. The mentor will guide the interns to explore the possibility of using coffee as a painting medium. The interns will learn to prepare the medium by collecting coffee ground from nearby coffee shops and create artworks using coffee. The SIP interns will learn how to protect their work. An important part of this research project will involve building a website to promote the idea of using coffee as a medium and to display the interns’ artworks. The mentor will help in selecting art works for online exhibitions like Project Coffee Art.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Art appreciation, learning to use an unconventional medium and designing one’s own website, scientific investigation

URL: https://www.modernobysaulvillegas.com/, http://www.srijoni.com/

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ACS-03 (EEB)
Title: The Algae Society: BioArt & Design Exhibition with UCSC OpenLab Collaborative Research Center
Primary mentor: Rebecca Ora
Faculty advisor: Prof. Jennifer Parker
Location: Remote/online
Number of interns: 3

Project description:
At a time of ecological and environmental crisis, the political and policy process alone is too slow to guide a deep search for understanding and interventions that will save the planet and its species. In response, and as an interventionary practice, the diverse international group of artists, scientists, designers, and algae that constitute The Algae Society (http://algaesociety.org/) examine the human position in global ecology through the lens of our algal fellow travelers, with a view to ultimately adopting a post-human philosophical position and practice with human and algae as companion species. The SIP interns will help build data visualizations and models for The Algae Society upcoming exhibition at the Cameron Art Museum in Wilmington, North Carolina.

Tasks:
The SIP interns’ tasks will include: (1) exploring best practices and techniques for art and science collaborations; (2) create digital art and 3D assets for VR (virtual reality) and AR (Augmented Reality) and film; (3) work with and explore (remotely) The UCSB Algae Herbarium digital archive; and (4) research the effects of climate change on algae and the symbiotic relationship between algae and humans.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work

URL: http://algaesociety.org

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ACS-04 (EEB/CSE)
Title: Neuroscience/Art/Biology/Computer Science — Visualizing Sleep in Northern Elephant Seals
Primary mentor: Jessica Kendall-Bar
Faculty advisor: Prof. Terrie Williams
Location: Remote/online
Number of interns: 3

Project description:
This research project examines the first recordings of marine mammal sleep in the wild to learn about the natural behavior of northern elephant seals. These seals sleep while holding their breath underwater and their brain oxygen levels plummet to levels which would cause brain damage in humans. Our visualization is aimed at increasing scientific understanding as well as appreciation and admiration for our underwater counterparts. This project will merge computer science, art, and biology to analyze and visualize the behavior and brain activity of these wild animals.

Tasks:
The SIP interns will learn to score sleep and behavior, gain familiarity with programming languages such as R, Python, and Javascript for data analysis and visualization, and work collaboratively to design a front-end user interface for interactive data visualization. Depending on individual interests, a given SIP intern may focus primarily on design, biology, or programming tasks, but each intern will gain an overall understanding of the data visualization pipeline from data collection to processing, analysis, visualization prototyping, debugging, and final implementation.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, field work, lab work, statistical data analysis

URL: https://jessiekb.com

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ACS-05 (ENV)
Title: Cataloguing Mayan Medicinal Plants: Bridging the Gap between Indigenous Medicine and Contemporary Science
Primary mentor: Dr. Andrea Medina (UC Santa Barbara)
Secondary mentor: Juliette Riancho (Pacifica U.)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: Remote/online
Number of interns: 3

Project description:
This research project will engage high school students in the foundational process of setting up a medicinal plant reserve in a Maya jungle in the Yucatán peninsula. The SIP interns will assist in researching the active ingredients/chemical compounds of plants used in Maya communities. The research will also include current uses of such compounds (in synthetic forms) in pharmaceutical medications in order to contrast it with their use in today’s Maya medicine. The decipherment of hieroglyphic Maya writing has been a major tool to learn about this culture. The SIP interns will have an opportunity to use glyphs, and to explore their artistic creativity as they help create this repository of knowledge. Current world events, from the pandemic to mega-tourism-projects, are not only directly impacting the way the Maya peoples live, but they are also devastating the environment. Medicinal plants are at great risk of being lost. The aim of the reserve is to protect, reproduce, and expand the possibilities for the continued existence of these medicinal plants.

Tasks:
The SIP interns tasks will include: (1) participating (online) in ethnobotanical field research in a Mayan jungle in Yucatán with the help of their primary and secondary mentor who will be in that location; (2) biochemical research; (3) direct (online) and indirect (online) interactions with Maya healers; (4) creating art; and (5) recording repositories of knowledge from diverse cultural paradigms. The SIP interns on this research project are expected to collaborate with the interns on the related ACS-06 (ENV) research project.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ACS-06 (ENV)
Title: Creativity in Holistic Healing: Designing Access to Mayan Medicinal Plants through Interactive Tools and Guides
Primary mentor: Juliette Riancho (Pacifica U.)
Secondary mentor: Dr. Andrea Medina (UC Santa Barbara)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: Remote/online
Number of interns: 3

Project description:
The Yucatán jungle is home to myriad plants native to the Mayan region, many of which contain medicinal and healing properties. The aim of the research project is to create a comprehensive labeling system and interactive profile of the plants found within the Santa Rosa plant reserve project that takes into account scientific and cultural dimensions of healing. The SIP interns will engage in a two-part creative project that promotes accessibility and enhances healing autonomy for visitors of the plant reserve. The interns on this research project will work closely with the interns assigned to the sister project ACS-06 (ENV) in order to create user-friendly labels for the native plants to be displayed throughout the reserve. The interns will also design an interactive, multi-modal healing tool and biochemical map for use by reserve visitors. The aim of this tool is to support users in identifying their various somatic ailments and matching them to plants across the reserve based on their healing properties. A holistic healing philosophy informed by the Maya culture forms the basis of this research project which promotes mindfulness, multiplicity, and reciprocity with nature.

Tasks:
The SIP interns tasks will include: (1) conducting research on indigenous healing philosophies and modalities; (2) interacting directly (online) and indirectly (online) with Maya healers; (3) creating a comprehensive labeling system for medicinal plants; (4) match the healing properties of various plants with corresponding somatic illnesses/ailments; and (5) designing an interactive, multi-modal tool for visitors to use within the reserve.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Astronomy & Astrophysics

Project code: AST-01
Title: What Happens Around Supermassive Black Holes
Primary mentor: Dr. Martin Gaskell
Location: Remote/online
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:
SIP intern involvement in the project will consist of analyzing multi-wavelength spectral observations of relatively nearby actively accreting supermassive black holes to try to understand the emissions and how the black holes grow. This work will involve compiling data sets, applying corrections, making statistical estimates of parameters, and comparing the results with theoretical models of processes going on around black holes.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: http://campusdirectory.ucsc.edu/cd_detail?uid=mgaskell

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-02
Title: Cosmological Galaxy Simulations
Primary mentor: Clayton Strawn
Faculty advisor: Prof. Joel Primack
Location: Remote/online
Number of interns: 3

Project description:
Cosmological galaxy simulations have become increasingly meaningful in the last few decades, and mock “observational” tests of simulations can set meaningful constraints on how accurately the physical assumptions built into the simulation emulate the real universe. This project will use mock quasar/galaxy absorption spectra created with the new software TRIDENT to emulate observations of the region directly outside of galaxies proper but within their dark matter halo, the circumgalactic medium (CGM). The CGM is relatively difficult to observe, because gas is not dense enough to form stars, and therefore this region is only detected in absorption, so only by simulating this observed quantity can one evaluate the simulation’s CGM.

Tasks:
Interns will be helping to develop software to analyze the circumgalactic medium (CGM) of a variety of simulation codes. We have access to many codes through the AGORA project, and our main task for the next AGORA paper is to analyze the differences caused by the different code implementations of the same galaxy initial conditions. This will include opportunities to contribute to the project github account (linked below), to learn how to remotely access remote supercomputers, where the simulation data will be stored, and to compare and contrast the different codes.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming

URL: https://github.com/claytonstrawn/quasarscan

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-03
Title: Identifying Exoplanets with Detectable Precession Rates with Dynamical and Light Curve Modeling of Multi-Planet Systems
Primary mentor: Patrick Maragos (U. of the Pacific)
Faculty advisors: Prof. Daniel Jontof-Hutter (U. of the Pacific), Prof. Raja GuhaThakurta
Location: Remote/online
Number of interns: 3

Project description:
Exoplanet transit surveys like Kepler and TESS have discovered hundreds of compact multi-planet systems, in which several planets are in a transiting configuration. As a planet’s orbit precesses due to the gravity of its neighbors, its transit impact parameter may change by a detectable amount over time. In this research project, the SIP mentor and interns will calculate the rate of change of impact parameter for hypothetical systems using N-body simulations, and use the results to identify systems of potentially detectable changes in impact parameter from Kepler and TESS. Future transit light curves of these systems may constrain the planetary masses or hint at additional undetected planets.

Tasks:
The SIP interns will do the following: (1) explore the effect of orbital periods on transit light curve; (2) explore the effects of orbital-to-stellar radius ratio, inclination, eccentricity, and argument of periastron on the transit light curve; (3) write code to convert inputs for the Batman Python package into impact parameter, and measure changes in transit depth and transit duration from Batman output; (4) learn to construct dynamical models of planets with the Rebound software; (5) get a simple simulation running and print out orbital elements over time; (6) write code to measure inclination variations from simulation output, plot inclination and impact parameter variations over time, and give examples of transit curves with Batman; and (7) apply these codes to some known exoplanet systems.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-04
Title: Supernovae
Primary mentor: Matthew Siebert
Faculty advisor: Prof. Ryan Foley
Location: Remote/online
Number of interns: 3

Project description:
Type Ia supernovae are exploding stars that are “standard candles” and therefore essential for understanding the expansion history of the Universe. The SIP interns will use a large spectroscopic dataset to explore the diversity of these phenomena. This will allow us to improve these Type Ia supernova events as cosmological distance indicators.

Tasks:
The SIP interns will develop software tools for working with spectroscopic supernova data. The interns will also learn a variety of advanced statistical data analysis techniques that are useful for analyzing large datasets like these.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://sites.google.com/ucsc.edu/transients/home?authuser=0

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-05
Title: Modeling the Stellar Kinematics of the Thick Disk and Halo of the Andromeda Galaxy
Primary mentor: Kaela McConnell (Yale U.)
Faculty advisor: Prof. Raja GuhaThakurta
Secondary mentor: Chiara Villanueva
Location: Remote/online
Number of interns: 3

Project description:
The kinematics of the resolved stellar population within a galaxy help us to understand the galaxy’s evolutionary history and formation. For example, there is considerable debate about the external and internal factors that can cause dynamical heating of stellar disks (e.g., molecular clouds, central bar, dwarf satellite bombardment, dark matter substructure). Using Hubble Space Telescope photometric data from the Panchromatic Hubble Andromeda Treasury (PHAT) survey and Keck DEIMOS spectroscopic data from the Spectroscopic and Photometric Landscape of Andromeda’s Stellar Halo (SPLASH) survey, the mentor’s research group has measured the line-of-sight velocities of approximately 10,000 stars in the nearby Andromeda galaxy (M31). This research project will entail detailed analytical and numerical modeling of the kinematics of red giant branch stars in M31’s thick disk and halo.

Tasks:
The SIP interns will: (1) make modifications to the existing Python code (stand alone files and Jupyter notebooks) that the mentors have developed to model the kinematics of M31’s thick disk of RGB stars; (2) add a dynamically hot halo component to the model; and (3) use a maximum likelihood framework to fit the model to the mentor’s group’s database of radial velocities of M31 RGB stars from the SPLASH and PHAT surveys.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://aas237-aas.ipostersessions.com/Default.aspx?s=04-A2-B8-DC-EE-2B-E5-AF-A5-83-93-E4-D3-99-B4-DC

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-06
Title: Broad Emission Line Sources (BELS) and Rare Emission Lines in Keck Spectra (RELIKS) of the Andromeda and Triangulum Galaxies
Primary mentor: Olivia Gaunt (Wellesley Coll.)
Faculty advisor: Prof. Raja GuhaThakurta
Secondary mentor: Khang Ngo
Location: Remote/online
Number of interns: 3

Project description:
What fills the space between stars in a galaxy? The tenuous gas and dust that fills this space is referred to as the interstellar medium (ISM). This project focuses on understanding the ionized gas component of the ISM in the disks of the nearby Andromeda (M31) and Triangulum (M33) galaxies. The SIP interns will work with multi slit spectra obtained by the mentoring team using the DEIMOS instrument on the Keck II 10-m telescope. The interns will use Python spectroscopic data analysis techniques to detect and carry out an investigation into the nature of a mysterious set of rare very broad emission lines in M33 and other rare/weak emission lines in both M31 and M33. They interns will explore the ultraviolet and X-ray properties of these rare sources using archival GALEX and Chandra data, respectively.

Tasks:
The SIP 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 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. The SIP interns on this research project will work closely with the interns on a related research project: AST-15.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.astro.ucsc.edu/faculty/index.php?uid=pguhatha

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-07
Title: Using the Canada-France-Hawaii Legacy Survey to Study Distant RR Lyrae Stars in the Halo of the Milky Way Galaxy
Primary mentor: Tawny Sit
Faculty advisors: Prof. Raja GuhaThakurta, Prof. Eric Peng (Peking U., China)
Location: Remote/online
Number of interns: 3

Project description:
Studies of the density profile, substructure, and kinematics of the Milky Way’s extended stellar halo tell us about our Galaxy’s accretion history and dark matter content. It has long been recognized that RR Lyrae stars can serve as useful tracers of the Milky Way’s stellar halo. These stars have a characteristic periodic pattern of brightness variations that distinguish them from other astronomical sources of comparable apparent brightness and color. Moreover, RR Lyrae are excellent standard candles, and they can also be used to measure the chemical abundance of the halo. The Canada-France-Hawaii Legacy Survey (CFHLS) used the 3.6-m Canada-France-Hawaii Telescope and MegaCam imager to obtain a series of deep images in five filters (ugriz) along four lines of sight. In this research project, SIP Interns will use the CFHLS database to study distant RR Lyrae stars.

Tasks:
The SIP interns will analyze CFHLS ugriz-band light curves of known RR Lyrae that were discovered in the Pan-STARRS-1 (PS-1) survey, search for new distant RR Lyrae in the CFHLS database that are fainter than the PS-1 detection threshold, separate Milky Way halo RR Lyrae from background quasars on the basis of unfolded light curves, fit empirical RR Lyrae template light curves derived from SDSS observations to CFHLS RR Lyrae candidates, and analyze new CFHLS RR Lyrae in the Bailey diagram (amplitude vs. period).

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.astro.ucsc.edu/faculty/index.php?uid=pguhatha

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-08
Title: Using Hubble Space Telescope Images and Keck Spectra to Search for and Characterize Variable Stars in the Andromeda and Triangulum Galaxies
Primary mentor: Kevin McKinnon
Faculty advisor: Prof. Raja GuhaThakurta
Secondary mentors: Avi Patel (Haverford Coll.), Dr. Monika Soraisam (UIUC/NCSA)
Location: Remote/online
Number of interns: 3

Project description:
Through the SALVATION survey, the mentor’s research group has been characterizing transient and variable stars (i.e., stars whose brightness changes over time) in the direction of our nearest galactic neighbor, Andromeda. Stars change brightness over time for many reasons (mass transfer from a companion, supernova explosion, physical instabilities/pulsations, etc.), and studying their properties allows us to understand new stellar physics and the environments that produce these interesting objects. While there are many telescopes that are currently measuring brightness fluctuations to detect variables and transients, we have developed another technique to identify possible targets; specifically, we will identify stars that have large offsets between their brightness measurements from the Hubble Space Telescope and those inferred from Keck DEIMOS spectroscopic observations. With data from the PHAT (photometry) and SPLASH (spectroscopy) surveys for millions of stars in the Andromeda (M31) and Triangulum (M33) galaxies, we plan to identify hundreds — if not thousands — of potential variable stars. This will greatly improve our statistics on variables in M31/M33 and allow us to create a catalogue of targets to track in the future.

Tasks:
The SIP interns will explore stellar spectroscopic and photometric properties for many different types of stars with a focus on those that change brightness over time (for a number of reasons). The interns’ tasks will include learning the basics of stellar evolution and stellar structure, and learning how to handle and manipulate photometric data from the Hubble Space Telescope and spectroscopic data from the Keck DEIMOS spectrograph. Ultimately, the group will produce an astronomical catalogue of potentially-variable/transient stars in our neighbouring galaxies.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.astro.ucsc.edu/faculty/index.php?uid=pguhatha

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-09
Title: The Globular Cluster Systems of Virgo Cluster Dwarf Galaxies
Primary mentor: Prof. Eric Peng (Peking U., China)
UCSC faculty contact: Prof. Raja GuhaThakurta
Location: Remote/online
Number of interns: 3

Project description:
Star clusters are collections of thousands to millions of stars formed together and still bound together by their gravity. The oldest and most massive star clusters are called “globular clusters” (GCs) for their round appearance. GCs can be seen at much greater distances than individual stars, because they shine with the combined luminosity of many stars coming from a relatively small amount of volume. This project will look for GCs around low-luminosity galaxies in the nearest cluster of galaxies, the Virgo cluster. One of the challenges in finding star clusters around nearby galaxies is that the brightness of the galaxy itself gets in the way. In the project, the SIP interns and mentors will model the smooth galaxy light and subtract it from the images in order to better find faint star clusters.

Tasks:
The SIP interns will work with images of galaxies in the Virgo cluster from the Next Generation Virgo cluster Survey (NGVS), a deep survey of the entire Virgo cluster with the Canada-France-Hawaii Telescope (CFHT). Using cutout images of the galaxies, the interns will use custom software (IRAF’s ELLIPSE and its modification, ISOFIT) to model galaxy light. The SIP interns will then use the software Source Extractor to find globular star clusters in the images.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.ngvs-astro.org/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-10
Title: Using Difference Imaging to Study Photometrically Variable Stars in Star Clusters in the Andromeda Galaxy
Primary mentor: Dr. Monika Soraisam (UIUC/NCSA)
Faculty advisor: Prof. Raja GuhaThakurta
Secondary mentor: Joseph Liu (Santa Clara U.)
Location: Remote/online
Number of interns: 3

Project description:
The mentor’s research group has been exploring photometrically variable stars in the Andromeda galaxy (M31). Photometrically variable stars are those that undergo variations, often repeated or even strictly periodic variations, in their brightness due to pulsations. Recent large time-domain surveys (e.g., the POMME survey with the Canada-France-Hawaii Telescope and MegaCam imager) have discovered thousands of variable stars in M31. In addition, the Hubble Space Telescope (HST) has been used to carry out a large near UV/optical/near IR imaging survey called PHAT that covers a fraction of the bright disk of M31, and the mentor’s group has led a large Keck DEIMOS spectroscopic survey of M31 stars called SPLASH. The combination of variable star light curve data from time-domain observations, HST brightness and color measurements, and Keck spectra presents a unique opportunity to understand the nature of these variable stars.

Tasks:
The SIP interns will cross match variable stars found in one or more of the time-domain surveys with HST PHAT survey photometric data and Keck DEIMOS spectroscopic data. The matched data set can then be used to construct a variety of color-magnitude diagrams (CMDs) and color-color diagrams. The SIP interns will work on new ways to identify variable stars in the PHAT dataset. They will group the variable stars according to CMD location and study systematic trends in light curve properties across and within the different groups.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.astro.ucsc.edu/faculty/index.php?uid=pguhatha

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	OFF	ON	ON	ON	ON	ON

 

Project code: AST-11 (a, b)
Title: Milky Way Halo RR Lyrae: (a) Measuring the Completeness Fraction and Quasar Contamination Rate of the Photometric NGVS Dataset, and (b) Radial Velocity Measurements from Time Series Spectroscopy with the Keck and Lick Telescopes
Primary mentors: (a) Yuting Feng, and (b) Joseph Salinas
Faculty advisors: Prof. Raja GuhaThakurta, Prof. Eric Peng (Peking U., China)
Secondary mentor: Douglas Grion Filho
Location: Remote/online
Number of interns: 4

Project description:
Despite its static appearance at first glance, the Universe is constantly changing. Monitoring the sky for these changes is time consuming, but doing so allows us to identify unique celestial phenomena. Most images taken of the sky are not suitable for studying the “time-domain” because they are not taken with an appropriate spacing in time (cadence). The Next Generation Virgo Cluster Survey (NGVS), a deep, multi-color imaging survey of the closest cluster of galaxies, adopted an observing strategy that spaced observations for a given field over a time period of hours to years. While not designed for time-domain studies, this observing strategy allows us to look for things in the sky that change in brightness. Part (a) of this research project will analyze two different types of variability: (1) RR Lyrae variable stars in the outskirts of our Milky Way galaxy, excellent probes of our Galaxy’s assembly history via the cannibalism of smaller galaxies, and (2) variability of distant quasars caused by stochastic accretion of material onto the supermassive black holes that power them. Part (b) of this research project will use spectra obtained by the mentors’ research group to study the dynamics of Milky Way halo RR Lyrae.

Tasks:
Part (a): Two of the SIP interns will analyze realistic simulated time series photometry of RR Lyrae and quasars derived from well studied known RR Lyrae and quasars. These simulated data will mimic the relevant characteristics (cadence, photometric errors) of the NGVS deep time series imaging dataset. The interns will apply standard data analysis techniques to these simulated data to measure completeness and contamination fractions in the NGVS RR Lyrae sample. Part (b): Two of the SIP interns will analyze time series Keck/ESI, Keck/DEIMOS, and Lick Shane/Kast spectra of bright RR Lyrae to monitor radial velocity variations of their photospheres during their pulsation cycle. The interns will also analyze deep Keck/ESI spectra of faint/distant MW halo RR Lyrae discovered in the NGVS dataset.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.astro.ucsc.edu/faculty/index.php?uid=pguhatha

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-12
Title: Optimizing the Search for Gamma-Ray Bursts at Very High Energy
Primary mentor: Prof. David Williams
Location: Remote/online
Number of interns: 3

Project description:
Very high-energy (VHE) gamma rays are used to study some of the most powerful systems in the Universe, including pulsars, supernova remnants, and the black holes at the centers of galaxies. They have recently been observed from a few gamma-ray bursts (GRBs), as well. VHE gamma rays are also the most energetic form of electromagnetic radiation observed from astrophysical sources, a trillion times more energetic than optical light and a million times more energetic than X-rays. Using data from the VERITAS VHE gamma-ray telescopes, the interns will investigate ideas for improving the way the data are analyzed, with the goal to develop analysis methods that are more sensitive, in particular for GRBs. These studies will primarily use data from the Crab Nebula, a strong and steady VHE gamma-ray source powered by the Crab Pulsar. If time allows, the methods developed may be applied to some GRBs of interest. Because the project uses data from the VERITAS Collaboration, there will be some limits and constraints on what results can be presented in various public contexts, consistent with the VERITAS Collaboration publication policies.

Tasks:
The SIP interns will learn to use computer programs for analyzing the VERITAS data and run the analysis on data sets from one or more of the objects of interest. They will also learn to inspect the output of programs which test the VERITAS data quality in order to remove poor-quality data (usually the result of bad weather) from the sample. They will compare different ways of doing the analysis in order to identify an optimum approach that gives the best (in the sense of most definitive) results. In doing so, the SIP interns will gain familiarity with standard tools used for astrophysics and particle physics data analysis and with working in the Linux computing environment.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: http://scipp.ucsc.edu/~daw/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-13
Title: Spectroscopy of Milky Way Halo Stars in HALO7D: Dynamics, Dark Matter, Accretion History, and Chemical Enrichment
Primary mentor: Miranda Apfel
Faculty advisors: Prof. Raja GuhaThakurta, Prof. Connie Rockosi
Secondary mentor: Kevin McKinnon
Location: Remote/online
Number of interns: 4

Project description:
The Milky Way galaxy which we call home is embedded within a vast and massive halo that is composed of mostly dark matter with a (literally!) light frosting of old, chemically anemic stars. The 3D velocities and surface chemical composition of these stars contains information about the accretion history, dark matter content, and chemical enrichment history of our Galaxy. The mentor’s research collaboration is using precise sky positions (astrometry) of these stars from the space-based Gaia mission and Hubble Space Telescope over a 10+ year baseline to measure their proper motions, two components of their velocity. Earlier this year, the group obtained spectra of these stars using the Keck II 10-meter telescope on Mauna Kea, Hawaii and the DEIMOS spectrograph. These stellar spectra will be used to measure the third (line-of-sight or radial) velocity component of these stars and their detailed chemical abundance patterns.

Tasks:
Through this research project, the SIP interns will become intimately familiar with astronomical spectra. They will use the Interactive Data Language (IDL) program zspec to measure/vet measurements of stellar radial velocities and learn to recognize and flag residual instrumental and atmospheric artifacts. They will compare the performance of the IDL-based spec2d and Python-based PypeIt data reduction pipelines. Time permitting, the SIP interns will learn about the basics of chemical abundance measurements from stellar spectra.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.astro.ucsc.edu/faculty/index.php?uid=pguhatha

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-14
Title: Weak CN Stars, Carbon Stars, and Other Exotic Stars in M31, M33, and the LMC
Primary mentor: Douglas Grion Filho
Faculty advisor: Prof. Raja GuhaThakurta
Secondary mentors: Antara Bhattacharya, Stan Rinehart
Location: Remote/online
Number of interns: 3

Project description:
The Andromeda galaxy (M31), the nearest galaxy larger than our own galaxy, its companion the Triangulum galaxy (M33), and the Large Magellanic Cloud (LMC), a Milky Way dwarf satellite galaxy, serve as an excellent laboratories for the study of stellar populations including rare stars. Carbon stars constitute one such class of rare stars. The distinguishing characteristic of these stars is their atmosphere contains carbonaceous molecules such as CN, CH, and C_2 that make their presence known via broad absorption bands in the spectra of these stars. The mentor’s research group, working with previous SIP interns, has discovered a new class of rare stars called “weak CN” stars in which the CN spectral absorption feature at about 8000 Angstrom is much weaker than in the spectra of carbon stars. The initial discovery/classification of the weak CN stars was based on visual inspection of spectra and the group has since been working on automated classification with the goal of using state-of-the-art machine learning methods. Other rare stars in M31, M33, and the LMC include two classes of emission line stars.

Tasks:
The SIP interns will analyze 1D spectra obtained with the DEIMOS spectrograph on the Keck II 10-meter telescope and the Hydra spectrograph on the CTIO Blanco 4-meter telescope. The interns will work with visually-classified and machine-classified populations of rare stars in M31, M33, and the LMC. The interns will use existing Python software and write custom software to analyze and compare these M31, M33, and LMC samples in terms of the following diagnostics: various HST and ground based color-magnitude diagrams (with theoretical stellar tracks overlaid), fraction relative to normal oxygen-rich stars, co-added spectra, kinematics (line-of-sight velocity dispersion and asymmetric drift relative to neutral hydrogen), and others.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.astro.ucsc.edu/faculty/index.php?uid=pguhatha

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-15
Title: Kinematical, Chemical, and Physical Properties of the Ionized Gas Disks of Andromeda and Triangulum
Primary mentor: Khang Ngo
Faculty advisor: Prof. Raja GuhaThakurta
Secondary mentor: Olivia Gaunt
Location: Remote/online
Number of interns: 3

Project description:
The interstellar medium (ISM) in a galaxy is the gas and dust that fills the space between stars. This research project focuses on understanding the ionized gas disks of the Local Group disk galaxies Andromeda (M31) and Triangulum (M33) galaxies. The SIP interns will work with multi slit spectra obtained by the mentoring team using the DEIMOS instrument on the Keck II 10-m telescope. The interns will use Python techniques to detect and characterize the spectral emission lines that are commonly associated with the ionized gas ISM component of galaxies. The interns will compare M31 and M33’s ionized gas disk kinematics to the kinematics of their neutral atomic (HI) and molecular (CO) gas disks. They will draw conclusions about the rotational dynamics, chemical composition, and physical properties of M31 and M33’s ionized gas disks.

Tasks:
The SIP 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 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. The interns will fit constrained Gaussian mixture models to the spectra, analyze the Doppler shifts of the emission lines as a function of sky position, and analyze emission line ratios in the so-called BPT diagram to constrain the physical and chemical properties of the ionized gas. The SIP interns on this research project will work closely with the interns on a related research project: AST-06.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://www.astro.ucsc.edu/faculty/index.php?uid=pguhatha

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: AST-16
Title: Looking for Evidence of Intermediate Mass Black Holes in Star Clusters in the Virgo Cluster
Primary mentor: Vivian Tang
Faculty advisors: Prof. Raja GuhaThakurta, Prof. Piero Madau
Secondary mentors: Yuting Feng, Prof. Eric Peng (Peking U., China)
Location: Remote/online
Number of interns: 3

Project description:
Research over the last few decades has established that galaxies comparable in mass to the Milky Way host massive central black holes whose mass M_BH is tightly correlated with their host galaxy mass M_gal. Extrapolating this M_gal–M_BH relation down to star clusters of mass 10⁶ M_sun would suggest that star clusters should host intermediate mass black holes: M_BH ~ 10³ M_sun. However, observational evidence for/against the presence of intermediate mass black holes has remained the subject of vigorous debate. One useful observational signature of intermediate mass black holes in dense star clusters is the temporary light burst caused by a tidal disruption event (TDE): the tidal disruption of an unfortunate star that strayed too close to the black hole’s event horizon. The Next Generation Virgo Cluster Survey (NGVS) has obtained repeat brightness measurements of tens of thousands of star clusters in the Virgo cluster of galaxies.

Tasks:
The SIP interns will carry out the following set of theoretical calculations under the close guidance of the primary and secondary mentors: (1) trying out different slopes for the M_gal–M_BH relation to predict the abundance and mass of black holes in Virgo star clusters, (2) probability of TDEs given the density of stars in the vicinity of the central black hole, and (3) simulating the cadence of the NGVS observations on the theoretically predicted set of TDEs.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: http://www.ucolick.org/~pmadau/Research_Highlights.html

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Biomolecular Engineering

Project code: BME-01
Title: SARS-COVID-19 Variants Study
Primary mentor: Gepoliano Chaves
Faculty advisor: Prof. Nader Pourmand
Location: Remote/online
Number of interns: 4

Project description:
In response to the COVID-19 pandemic, this research group has been exploring the possibility of developing a DNA-sequencing platform to detect the Coronavirus based on a DNA-sequencing method called NGS, Next Generation Sequencing. In this research project, the group will make use of some of the knowledge gained in working on the development of a Coronavirus detection platform to present the SIP interns with basic strategies to study the genome of the virus. These strategies include the design of primers to amplify genomic regions of interest, and the notion of variant call, identifying Single Nucleotide Polymorphisms (SNPs), which can explain the inter-species jumps of viral strains making them prone to infect different species.

Tasks:
The SIP interns will work on the following tasks: (1) primer design for genomic region amplification; and (2) identification of Single Nucleotide Polymorphisms in the genome of the Coronavirus. They will run bash and R scripts to identify variants in the viral genome.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	OFF	ON	ON	ON	ON	ON	ON	ON

 

Project code: BME-02
Title: Machine Learning Model for Predicting Breast Cancer
Primary mentor: Sam Teymoori
Faculty advisor: Prof. Benedict Paten
Location: Remote/online
Number of interns: 4

Project description:
Artificial intelligence, such as machine learning or deep learning, offers incredible value to the genomics industry. By using machine learning techniques, it is possible to analyze a great amount of genomics-related data, which can be found in publicly available research papers. In this project, we will introduce the mathematical concepts underlying the Logistic Regression, and through use of Python, we will make a predictor for malignancy in breast cancer. For this project, we will use the “TCGA expression datasets,” provided by the UCSC genomics lab database, which comprises gene expression data for twenty thousand tumor and normal samples processed using the exact same genomics pipeline so they can therefore be compared to each other.

Tasks:
The SIP interns will go through a machine learning model to make a predictor for malignancy in breast cancer. First, the interns will make the pre-process. Second, the interns will make determinations and selections of the appropriate machine learning model. Third, the interns will train the model. Finally, the interns will test the model to calculate the efficacy of their machine learning task.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: BME-04
Title: Bioinformatics Pipeline to Calculate the Frequency of Viral Variants of Concern Versus Time in a Geographic Location
Primary mentor: Danilo Coelho (Fed. U. of Viçosa, Brazil)
Secondary mentor: Dr. Gepoliano Chaves

Location: Remote/online
Number of interns: 4

Project description:
In the past few years, several countries have been exposed to various segregated viral epidemics. Examples include the HIV epidemic in the 1980s, dengue in the 1990s, and SARS in the early and middle 2000s. All these epidemics have hit Brazil, but the most notable viral epidemics in the country have been the Zika virus in 2015–2016 and the current SARS-CoV-2 pandemic. As part of an international effort led by researchers in Brazil and the University of California Santa Cruz to build an international capacity in genomic sequencing analysis and epidemiology, this research project aims to build a pipeline for the calculation of the frequency as a function of time of Variants of Concern (VOC) of viruses endemic to Brazil, such as Zika and SARS-CoV-2.

Tasks:
In this research project, the SIP interns will: (1) learn to use statistical analysis techniques that are used in epidemiology; (2) analyze the molecular basis for the establishment of a variant of concern (VOC): (3) analyze the three-dimensional structure of viral proteins that explain increase in viral transmissibility and viral evasion of the immune system; and (4) use informatics to calculate frequency of a VOC a function of time.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	OFF	OFF	ON	ON	ON	ON	ON	ON

 

Project code: BME-05
Title: Building a Web Application for Visualization of SARS-CoV-2 Variants of Concern for Use in the Context of a Middle Income Country
Primary mentor: Prof. Jaime Amorim (Fed. U. of W. Bahia, Brazil)
Secondary mentor: Dr. Gepoliano Chaves

Location: Remote/online
Number of interns: 3

Project description:
It is thought that the present COVID-19 pandemic emerged from a “zoonotic jump” from a wild animal to humans in an animal market in the Chinese province of Hubei in 2019. These zoonotic jumps happen as a result of mutations in the genetic material of the virus to provide viral adaptation to its host. Depending on the threat they represent, these mutations can be called variants of concern (VOC) because, at the same time as they provide adaptation, they may threaten human life as is the case right now with the global pandemic. Health policies should take advantage of genomic information that track VOCs that are potentially more infective than others and therefore dangerous to the public. Geographic regions with increases in the frequency of VOC should implement more rigorous isolation policies. In this research project, the SIP interns will be exposed to the process of construction of a web application to visualize the frequency of VOC with time using genomic sequencing data.

Tasks:
The SIP interns will: (1) download data from a database; (2) align data to the reference genome; (3) identify variants in the regions they were isolated from; (4) compare the variants of a region to a list of VOC; (5) learn to use bioinformatics to count variants in these regions; and (6) calculate VOC frequency in the geographic region of interest. Because the mentor’s group works on sequencing SARS-CoV-2 in the Brazilian state of Bahia, the SIP mentor and interns will look particularly closely at sequencing data from this state.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Chemistry & Biochemistry

Project code: CHE-01
Title: Application of Machine Learning in Developing Promising N-Doped Carbon Catalysts for the Oxygen Reduction Reaction
Primary mentor: Mingpeng Chen
Faculty advisor: Prof. Yat Li
Location: Remote/online
Number of interns: 3

Project description:
The oxygen reduction reaction (ORR) is the cathodic reaction of a fuel cell. It is a four-electron-transfer process that generates a high energy barrier and limits the reaction efficiency. Platinum is well known as the most efficient catalyst for ORR and is often used as the benchmark for ORR. However, its high cost and scarcity has limited its applications. In addition, platinum-based catalysts suffer from problems such as time-dependent drift, CO deactivation, etc. A number of alternative materials have been explored to replace platinum. Among them, nitrogen (N) doped carbons have been demonstrated to be promising materials for ORR owing to its low cost, high abundance, and strong resistance to the poisoning of CO. In this research project, the SIP mentor and interns will employ machine learning to help understand how the concentration of N doping and ligand affect the ORR activity of N-doped carbon.

Tasks:
The SIP interns will: (1) understand the background of the oxygen reduction reaction; (2) understand the physical quantities researchers use to describe the activity of ORR catalysts; (3) generate enough structures for machine learning; and (4) use machine learning to train and find physical rules behind these data.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

URL: https://li.chemistry.ucsc.edu/

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Computational Media

Project code: CPM-01
Title: Game-Making Tools Survey
Primary mentor: Jared Pettitt
Faculty advisor: Prof. Nathan Altice
Location: Remote/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 you 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: None
Skills interns will acquire/hone: Computer programming

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	OFF	ON	OFF	ON	ON

 

Project code: CPM-02
Title:VR Game Development for Psychosocial Support of Preteens with Cleft Lip and/or Palate
Primary mentor: Tiffany Thang
Faculty advisor: Prof. Sri Kurniawan
Location: Remote/online
Number of interns: 4

Project description:
This research focuses on the development of a virtual reality (VR) game aimed at providing psychosocial support in the realm of self-confidence for preteens with cleft lip and/or palate (CLP). In collaboration with global CLP organization, Smile Train, we will be working on understanding how we can create a VR game that provides supplemental support to existing psychosocial support from psychologists and clinicians working with preteens with CLP. In this project, we will work with psychologists, clinicians and preteens with CLP in understanding how to develop a VR game that helps with developing and practicing self-confidence skills.

Tasks:
SIP interns can expect to gain knowledge in virtual reality, CLP, and assistive technologies through conducting literature reviews early in the program. Interns can also expect to learn the process of designing and developing a VR game through storyboarding and wireframing, and will learn how to create a 3D modeled VR environment using Unity and Blender.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: CPM-03
Title: Conversational UX Design
Primary mentor: Kehua Lei
Faculty advisor: Prof. David Lee
Location: Remote/online
Number of interns: 3

Project description:
The goal of this research is to explore novel conversational user experience (UX) design. Conversational UX in this project refers to conversational user interfaces (UIs) and interaction modes that support text-based communications. We now have two research directions. The first one is designing richer conversational features to enable large-scale units in chat-based UIs. We developed a platform for students to attend online sessions that provide one-to-many mentorship experiences and full engagement without the typical chaos of group chat. The other direction is building a platform for users to create a chat group with chatbots that have different personalities. This could offer emotional supports to users. This research project will contribute to the field of human-computer interaction, conversational UX design, software testing, and code generation.

Tasks:
The SIP interns will do some or all of the following: (1) design conversational features for one of the platforms; (2) create dialogues for real scenarios; (3) design UIs on Figma; (4) conduct usability tests; (5) develop the platform using JavaScript and Angular framework; (6) identify the research contributions of the projects.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, field work, lab work

URL: https://tech4good.soe.ucsc.edu/

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: CPM-04
Title: Game Generation via Orchestration
Primary mentor: Isaac Karth
Faculty advisor: Prof. Adam M. Smith
Location: Remote/online
Number of interns: 3

Project description:
The SIP interns will contribute to the development and evaluation of a game generation program, using a new approach for applying generative design to the game orchestration problem [1] using the Game Boy as a target platform. The interns will author training data, evaluate existing software for examples of training data, use automated playtesting software to gather data, assist with the programming of the generative design software, and assist in evaluating the results. This research project will contribute to the fields of software testing, generative design, game design, and code generation. [1] A. Liapis, G. N. Yannakakis, M. J. Nelson, M. Preuss and R. Bidarra, “Orchestrating Game Generation,” in IEEE Transactions on Games, vol. 11, no. 1, pp. 48-68, March 2019, doi: 10.1109/TG.2018.2870876.

Tasks:
The SIP interns will do some or all of the following: (1) evaluate existing games for possible training data, (2) author additional training data, (3) gather experimental data on the results of the generation, (4) run machine playtesting experiments, (5) automate the formatting of playtesting reports, and (6) evaluate the results of generation and playtesting. Programming for this project will primarily use JavaScript and ClojureScript, though the training data authoring will primarily occur via GB Studio and there may be a small amount of scripting in Python. Interns can contribute to the project without programming, though prior experience with some kind of programming can be helpful.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming

URL: https://designreasoning.soe.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: CPM-05
Title: Automatic Audio Generation for Game Boy Programs
Primary mentor: Tamara Duplantis
Faculty advisor: Prof. Nathan Altice
Location: Remote/online
Number of interns: 3

Project description:
This research project will contribute to the fields of procedural audio, algorithmic music, digital musical interface design, and game generation. The SIP interns will contribute to the development and evaluation of a generative audio system targeting the Game Boy platform. The project will involve authoring example audio output, designing programs that generate the target audio output, integrating the resultant audio generators with a GB Studio game generation project, and exploring methods for generating procedural audio systems to be run on the Game Boy.

Tasks:
The SIP interns will do some or all of the following: (1) author example game audio output using Game Boy tracker software, (2) assist in the design of generative audio programs, (3) integrate audio output into a larger game generation project using JavaScript. This project as a whole will likely involve programming in JavaScript and C; however, the interns’ contributions will be limited to JavaScript. If interns do not have programming experience, they can still contribute substantially to the project if they have a strong musical background.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, field work, lab work

URL: https://www.soe.ucsc.edu/departments/computational-media

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

 

Project code: CPM-07
Title: Reinforcement Learning in Video Games
Primary mentor: Batu Aytemiz
Faculty advisor: Prof. Adam M. Smith
Location: Remote/online
Number of interns: 3

Project description:
The larger research project aims to ensure people don’t feel helpless playing video games. To accomplish this goal, the mentor is building a parkour video game with no combat, and developing an artificial intelligence (AI) system to play the game. The mentor plans to use AI to help the players instead of fighting against them. The SIP interns will assist in the creation of game levels in Unity game engine, and in the collection of data to train the AI network (by playing the game). Optionally, depending on individual interest, the SIP interns can help with AI development or game development.

Tasks:
The SIP interns will: (1) develop playable levels in Unity game engine; (2) create datasets by playing the game; create visualizations of the experimental results (optional); and (4) implement game features in Unity game engine.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming

URL: https://youtu.be/D7xiy2TY61g?t=2260

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

 

Project code: CPM-09
Title: SpokeIt: Preparing a Speech Therapy Game for Global Delivery
Primary mentor: Jared Duval
Faculty advisor: Prof. Sri Kurniawan
Location: Remote/online
Number of interns: 6

Project description:
Therapy is costly, time-consuming, repetitive, and difficult. Games have the power to teach transferable skills, can turn repetitive tasks into engaging mechanics, have been proven to be effective at delivering various forms of therapy, and can be deployed at large scales. Games move us. The SIP interns will work to bring the mentor’s research group’s speech therapy game, SpokeIt, into the world. SpokeIt (http://SpokeIttheGame.com) is a speech therapy game for children born with orofacial cleft. It has been in development for five years, has been studied clinically, and features cutting edge tools that can critically listen to speech. SpokeItTheGame has recently partnered with SmileTrain — an organization that has supported over 1.5 million free cleft surgeries — and is gearing up to be deployed around the world (it is nearly ready for launch on the App Store)! The SIP interns will primarily be working on translating SpokeIt for release on Google Play as well as working towards supporting new languages.

Tasks:
Depending on the SIP interns’ expertise and interests, there are many opportunities to work on the research project. All interns will be expected to work on polishing existing game content or creating new content as well as analyzing user studies and playtests. Some example tasks include working on animations, sprite sheets, game engine components, art assets, databases, and analyzing user study data. For development, the mentor’s research group works primarily in Xcode, Unity, and Android Studio. The group uses various Adobe applications for design work, such as Illustrator, XD, Photoshop, After Effects, and Character Animator. The SIP interns will work towards translating SpokeIt to work on Android devices and towards adding support for new languages. The interns will need to have access to the Adobe Creative Cloud, an Android device, and an Apple computer.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming

URL: https://jareduval.com/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Computer Science/ Computer Engineering

Project code: CSE-01
Title: Generative Adversarial Networks
Primary mentor: Saeed Kargar
Faculty advisor: Prof. Faisal Nawab
Location: Remote/online
Number of interns: 4

Project description:
Generative Adversarial Networks (GANs) represent a class of generative models that were introduced by Goodfellow et al. (2014). It is one of the most-cited papers in computer science (over 27,000 in February 2021), 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.” [1] They generate/create new data instances that resemble your training data. For example, GANs can create images of human faces that are statistically indistinguishable from real ones even though the faces in the GAN-created images are not real and don’t belong to any real person. GANs are a clever way of training a generative model by training two sub-models: the generator model that is trained to create/generate new instances, and the discriminator model that tries to classify the instances as either real (belong to the training set) or fake (fake/generated). In this method, the generator, which produces the target output, is paired with the discriminator which learns to distinguish between fake and real instances in an interesting way. The generator tries to fool the discriminator, and the discriminator tries to keep from being fooled. There are a large number of interesting applications of GANs to help one develop an intuition for the types of problems where GANs can be useful such as: (1) generate cartoon characters, (2) image-to-image translation, (3) text-to-image translation, (4) semantic-image-to-photo translation, (5) face frontal view generation, (6) generate new human poses, (7) photos to emojis, (8) photograph editing, (9) face aging, (10) super resolution, (11) photo inpainting, (12) video prediction, (13) 3D object generation, and many others.[2]

Tasks:
The SIP interns will learn: (1) the concept behind GANs, and (2) how to implement GANs from scratch. The interns will learn various deep learning concepts and tools — e.g., using the Keras library, pre-trained models such as the VGG19 network, and popular online tools such as Google Colab to solve programming problems. Furthermore, they will learn how to read a research paper and implement it. What the SIP interns will learn are: (1) Python programming; (2) machine learning frameworks such as TensorFlow and Keras; (3) data collection from online resources; (4) one of the most advanced topics in deep learning – i.e., GANs; (5) critical reading of research papers; and (6) collaborating effectively in a team research environment.

Required skills for interns prior to acceptance: Computer programming (preferred)
Skills interns will acquire/hone: Computer programming, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

 

 

Project code: CSE-04
Title: Spike Sorting Algorithm: Basis and Implementation
Primary mentor: Jinghui Geng
Faculty advisor: Prof. Mircea Teodorescu
Location: Remote/online
Number of interns: 3

Project description:
Electrophysiology in neuroscience is a way to study the electrical properties of the cells and tissues in the nervous system. To detect and characterize the neuronal activities, spike sorting algorithm is a common tool used to analyze electrophysiological data, and it is fundamental for brain-computer interface development. This research is part of a project for developing a real-time neuronal signal acquisition and stimulation device. The interns will develop Python wrapper and functions to benchmark and compare several popular sorting algorithms in runtime, resource and accuracy, and build a thresholding application for a small scale embedded system.

Tasks:
Interns will be doing the following: (1) understand the neuronal data from extracellular recording, (2) learn the basic techniques in each step of the sorting algorithm, (3) learn Python tools such as Google Colab, Jupyter Notebook, Docker and etc, (4) program in Python to build the benchmark environment and report the result, (5) program in C/C++ or Python to implement the thresholding application on an embedded device.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://braingeneers.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: CSE-05
Title: Origami Robot: Modeling and Simulation
Primary mentor: Samira Zare
Faculty advisor: Prof. Mircea Teodorescu
Location: Remote/online
Number of interns: 4

Project description:
Origami is a newly emerging field in robotics that can help when limited space is available. They have many applications, from solar panels to medical devices. These deployable structures are able to move and change their shapes and structures based on their environment. For instance, solar origami panels can become compact to transfer and then deploy to their final structure. The mentor’s research group designs, models, and develops a dynamical simulation in Autodesk Inventor and uses Python to analyze and understand their movements.

Tasks:
The SIP interns’ primary tasks will be learning Autodesk Inventor and how to use Python to analyze the simulation data. Their secondary tasks will be to come up with Origami design ideas and apply a dynamical simulation to understand them. Finding an origami design that can be applied to real-world problems could be challenging. They can be too complex to control and model or too simple to perform any movement.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: CSE-06
Title: Bio-Inspired Spiking Neural Network Based on Memristors with Short-Term Plasticity for Audiocortical Processing
Primary mentor: Peng Zhou
Faculty advisor: Prof. Sung-Mo Kang
Location: Remote/online
Number of interns: 3

Project description:
The mentor’s research group is developing a bio-inspired spiking neural network for audiocortical processing based on memristors. Mammals and birds can detect the direction of a sound source based on coincidence detection in spiking neural networks (SNNs) with short-term plasticity (STP). Memristor, the fourth fundamental electrical element, is widely used in the area of neuromorphic computing. Aiming to overcome the bottleneck of the von Neumann architecture and the end of Moore’s law, neuromorphic computing emulates the human brain. It takes advantage of the brain’s high-density, low-power, and parallel computing. The SIP mentor and interns will simulate the memristor as the synapse model and emulate the sound localization spiking neural networks. This research project will be developed in Python and Brian2. It is exciting to emulate the function of actual human/animal brains!

Tasks:
The SIP interns will: (1) learn to use Python for programming; (2) understand the concept of the memristor and simulate the memristor; and (3) learn to build spiking neural networks and emulate a sound localization spiking neural network.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://nisl.sites.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	OFF	OFF	ON	ON	ON	ON	ON	ON

 

Project code: CSE-07
Title: RouteMe2: Providing Spatial Contextual Awareness for Assisted Transit Systems
Primary mentor: Fatemeh Mirzaei
Faculty advisor: Prof. Roberto Manduchi
Location: Remote/online
Number of interns: 3

Project description:
Navigating a public transit system can be confusing for everyone, especially in an unfamiliar environment (e.g., when visiting a new city). One needs to figure out which transportation lines to take to reach a destination, when and where to catch a bus or a train, when to exit, and how to negotiate transfers. For those with visual impairments or cognitive disabilities, these problems become even more daunting. They need to know nearby objects, have a better sense of their location, and make decisions based on this contextual information. The mentor’s RouteMe2 system tracks and navigates users in complex transit hubs and provides spatial contextual awareness for those in need. In this research project, the SIP interns will be helping with creating geometric shapes (tiles) on a map, defining spatial contextual information for tiles, improving the user interface of the system, and testing the system.

Tasks:
The SIP interns will participate in a practical scientific study and will become familiar with dealing with real world interesting challenges through their participation in this research project. The interns will learn to: (1) work with the RouteMe2 system; (2) define geometric shapes using Mapbox; (3) define spatial contextual information and associate it with specific tiles; (4) test the system; and (5) improve tile definition.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, field work

URL: https://vision.soe.ucsc.edu/welcome-ucsc-computer-vision-lab

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: CSE-08
Title: Deep Learning for Face Emotion Detection
Primary mentor: Negin Majidi
Faculty advisor: Prof. Manfred K. Warmuth
Location: Remote/online
Number of interns: 3

Project description:
Machine learning models have been shown to be powerful in many learning tasks such as pattern recognition, image classification, and face detection. Human emotion is usually displayed by face and felt by brain signals. We can use artificial intelligence systems to detect faces and extract emotions from faces. To build the models, we need to train an algorithm on a dataset and test it on some samples as our test set. In this research project, the SIP mentor and interns will build and train a convolutional neural network using Keras from scratch to detect face emotions. The data set consists of a collection of face images. The goal of the research project is to classify the images based on the emotion in the facial expression into a class. The project will use OpenCV to automatically detect faces in the images and make a bounding box for the faces. Afterwards, various CNNs will be trained to classify the faces into categories.

Tasks:
The SIP interns will: (1) learn useful programming tips in Python; (2) work collaboratively on programming tasks; (3) understand the concepts behind deep learning models, particularly CNNs; (4) learn to work with Keras and pre-trained CNN structures; (5) learn how to use Google Colab; and (6) develop familiarity with OpenCV.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Earth & Planetary Sciences

Project code: EPS-02
Title: Cloud Formation and Haze-Lake Interactions on Titan
Primary mentor: Dr. Xinting Yu
Faculty advisor: Prof. Xi Zhang
Location: Remote/online
Number of interns: 3

Project description:
Titan, the largest moon of Saturn, has an active hydrological cycle similar to Earth, but with liquid hydrocarbons instead of liquid water. Hydrocarbon clouds form in Titan’s atmosphere and are then rained down towards Titan’s surface, forming myriads of lakes and seas. Titan’s methane-nitrogen atmosphere also allows the formation of various organic compounds and eventually lead to the formation of complex organics, that forms Titan’s thick haze layers. In this research project, we will investigate the formation of hydrocarbon clouds in Titan’s atmosphere and the interactions between organic hazes and the lake liquids on Titan’ surface. We will use a combination of laboratory-generated data and direct observational data of the Cassini spacecraft to perform theoretical calculations to understand the above phenomena on Titan. Our goal is to better understand these physical phenomena with exotic materials in an exotic environment and to support future spacecraft missions to Titan, such as the Dragonfly rotorcraft mission, and ground-based observations.

Tasks:
Intern will perform the following tasks: (1) use Cassini data and previously published literature to compile the existing observed gas-phase species in Titan’s atmosphere and the lake compositions; (2) analyze collected laboratory data to compile the needed input for theoretical calculations; (3) perform theoretical calculations using laboratory-produced data and the above collected observational data and make predictions for future observations on Titan.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: http://www.xintingyu.com

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

 

Project code: EPS-04
Title: Fish Extinctions during Ancient Climate Change
Primary mentor: Prof. Matthew Clapham
Location: Remote/online
Number of interns: 3

Project description:
The fossil record contains multiple extinction events caused by climate change, a combination of ocean warming, acidification, and oxygen depletion. These extinctions are often selective, where some types of animals are severely affected but others are more resistant. Past selectivity patterns can help predict the types of animals that may be most vulnerable to future climate change. The goal of this research project is to compare the extinction of fishes with other animals in extinctions during the Cretaceous period, in order to determine whether fishes are especially vulnerable to climate change or are more resistant.

Tasks:
The SIP interns will compile a database of fossil fish occurrences from the Cretaceous period, collecting information about the age, geographic location, and possibly body size and/or diet/ecology, from published papers. The interns and mentor will use statistical methods to determine extinction selectivity, comparing fish extinctions to extinctions of other animals during multiple time periods, and evaluating the potential effect of body size or ecology on survival.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://people.ucsc.edu/~mclapham

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Ecology & Evolutionary Biology

Project code: EEB-01
Title: Should I Stay or Should I Go?
Primary mentor: Matthew Kustra
Faculty advisor: Prof. Suzanne Alonzo
Location: Remote/online
Number of interns: 3

Project description:
Alternative reproductive tactics are observed in many species, often as two distinct male types, a territory holding male and a sneaker male that sneaks mating opportunities from the territory holding male. The ocellated wrasse (Symphodus ocellatus), a Mediterranean fish species, has three alternative male reproductive tactics. Nesting males make nests, chase away sneakers, court females, and provide all parental care. Sneaker males try to join nesting males and females during mating events. Satellite males help the nesting male by chasing away sneakers but will also compete with them by joining mating events between the nesting male and females. The satellite male needs to balance helping the nesting male out, while also sneaking mating opportunities to gain some reproductive success. The mentor’s research group is investigating factors that may influence the satellite male’s decision on when and how often he should sneak. In this research project, the SIP mentor and interns will analyze underwater videos to record data on satellite male sneaking behavior as well as other attributes of the nest.

Tasks:
The SIP interns will primarily be analyzing underwater videos of fish mating behavior by recording spawning events as well as nest dynamics leading up to the spawning event. While collecting the data from these videos, the interns will learn how to properly manage collaborative data sets. Towards the end of the summer, the SIP interns will learn how to perform basic statistical analyses and make graphs in the R programming language. Additionally, the interns will learn more about behavior and evolution through paper discussions to put this research experience in the broader context of evolution and behavioral ecology.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://mattkustra.wordpress.com/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	OFF	ON

 

Electrical Engineering

 

Project code: ELE-02
Title: Rehabilitative Robotics
Primary mentor: Stephanie Herrera
Faculty advisor: Prof. Michael Wehner
Location: Remote/online
Number of interns: 3

Project description:
The superiority of robot-based rehabilitation over manual rehabilitation is now well-known. Lower extremity exoskeletons are an emerging technology to utilize as rehabilitative devices for patients with abnormal gaits from neuromuscular disorders, such as cerebral palsy, sclerosis, or stroke. Because most of the current systems have been designed with rigid structures and stiff actuation, they are not well suited for use in unstructured environments which can jeopardize human safety, comfort, and psychological acceptance. These concerns have begun a shift toward the inclusion of compliant elements to produce soft exoskeletons that are mainly composed of neoprene, elastic polymers, and innovative textiles. These soft technologies allow the exoskeleton to be moldable against the human body, increasing their degrees of freedom without adding bulkiness.

Tasks:
The SIP interns will analyze human gait dynamics and understand how to build a simplified model that allows for easier analysis. The interns will review case studies of rigid and soft lower-extremity exoskeletons to determine which mechatronic design, actuation, and control theory performs best while maintaining the patient safety. The interns will also be able to design their own rehabilitative robots making sure they are safe and compatible with the human body.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming, lab work

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ELE-03
Title: Renewable Energy and Power Systems
Primary mentor: Shourya Bose
Faculty advisor: Prof. Yu Zhang
Location: Remote/online
Number of interns: 3

Project description:
In order to reduce detrimental effects on the environment, power plants powered by fossil fuels are being phased out across the US and around the world in favor of renewable sources of energy such as solar and wind energy. The intermittent nature of renewable energy (the sun doesn’t always shine, and the wind doesn’t always blow) introduces new challenges in planning and operation of the electric power grid. The goal of this research project is to develop a plan for an electric power grid that contains solar and wind energy components, alongside large-scale batteries and other forms of power generation, so as to meet the electric power demand of consumers.

Tasks:
The SIP interns will review models of electric power grids that have renewable sources of energy attached to them. The interns will also review models of electric power demand from homes and industries. Based on the review, the interns will contribute to research about the modeling aspects of an electric power grid simulation which is being carried out by the mentor. At the conclusion of the summer research internship, the SIP interns will have a solid foundational understanding of how the electric power grid works.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://people.ucsc.edu/~yzhan419/

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ELE-04
Title: Nanophotonic Biosensors for Rapid Detection of Coronavirus SARS-CoV-2
Primary mentor: Ahsan Habib
Faculty advisor: Prof. Ahmet Ali Yanik
Location: Remote/online
Number of interns: 4

Project description:
The highly transmissible and pathogenic coronavirus SARS-CoV-2 has resulted in a pandemic of the acute respiratory disease called COVID-19 (coronavirus disease 2019). The first step in COVID-19 management is quick and accurate detection of SARS-CoV-2. Current diagnostic techniques rely primarily on polymerase chain reaction (PCR) tests which require the transport of a sample to a specialized laboratory resulting in massive detection delays. This research project aims to develop a label-free optical biosensor for the rapid diagnosis of COVID-19 disease at the point of care outside of the lab.

Tasks:
The SIP interns will work on the design of a nanophotonic biosensor. The interns will: (1) learn the basics of nanophotonic resonators; (2) learn about the optical waveguide design software Lumerical MODE; and (3) develop a nanophotonic biosensor using the Lumerical MODE software.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://scholar.google.com/citations?user=shPv4WEAAAAJ&hl=en/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Environmental Studies

Project code: ENV-01
Title: Improving Coastal Prairie Restoration for Increased Resilience to Drought
Primary mentor: Justin Luong
Faculty advisor: Prof. Michael Loik
Location: Remote/online
Number of interns: 4

Project description:
Ecological restoration seeks to alleviate loss of unique ecosystems through native plant reintroductions and invasive species control. However, restoration outcomes can be unpredictable and may become more so with climate change. Functional traits can help practitioners select plants based on traits that may survive better in a given environment. Because restoration practitioners are fund limited they cannot collect traits for plants they want to use and most plants have not yet been quantified. The group is interested in understanding if traits development of California native plants are constrained by evolutionary relationships or by climate. If traits did develop with constraints for climate or evolutionary relationship, practitioners can expand trait-based plant selection to unmeasured related species or those in similar climates.

Tasks:
The SIP interns will work on analyzing previously collected leaf samples for various leaf functional traits using the free imaging software: ImageJ. Leaf samples were previously collected from numerous plants along the California Coast. Understanding how leaf traits vary along a climatic gradient or within plant families can be important for improving ecological restoration and conservation by informing which species may be best suited for their local environment. The interns will meet regularly on Zoom with the mentor to learn proper measurement techniques and various lab activities. The SIP interns will read a scientific journal article once every 1 to 2 weeks for group discussion. By week 5, students will begin learning the basics of data analysis to report on their findings.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ENV-02
Title: Wildlife Conservation — Human-Conflict Assessment
Primary mentor: Dr. Veronica Yovovich
Faculty advisor: Dr. Prof. Chris Wilmers
Location: Remote/online
Number of interns: 3

Project description:
Mountain lions hold the dubious distinction of being California’s last top carnivore, and are a vital part of natural ecosystem balance and integrity. Human development threatens their future persistence by encroaching on habitat, killing mountain lions to prevent conflict with our livestock, and disrupting important dynamics. The mentor and her research group will use a variety of techniques to help understand mountain lion ecology and prevent human-mountain lion conflict. This project will involve working with human-wildlife conflict data to better understand patterns in when humans and mountain lions are at odds.

Tasks:
The SIP interns can expect to be involved in data processing associated with mountain lion research. The interns will become familiar with data entry, handling, and integrity in Excel, and may also contact the local wildlife management agency to solicit additional data. The exact research question is flexible and will depend on the interns’ interests. For example, the interns could use the conflict data to investigate spatial patterns in where conflicts occur, seasonal patterns, etc.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Statistical data analysis

URL: http://www.EcologyApplied.com

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	OFF	OFF	ON	ON	ON	ON	ON

 

Project code: ENV-03
Title: Causes and Impacts of Urban Sprawl
Primary mentor: Nazanin Rezaei
Faculty advisor: Dr. Prof. Adam Millard-Ball
Location: Remote/online
Number of interns: 3

Project description:
Urban form is one of the most central topics in the study of urbanism. Due to its negative environmental, social, and economic impacts, urban sprawl is considered as the unfavorable display of urban form. Most definitions of urban sprawl refer to the low-density and unplanned expansion of urban areas into suburbs. Moreover, it is widely recognized that transport infrastructure development plays a major role in shaping urban form. This research project attempts to figure out to what extent transport infrastructure affects urban sprawl.

Tasks:
The SIP interns will do background reading on the impacts of transportation on urban sprawl and identify the methods that have been used in the research articles. The interns can expect to be involved in gathering data on highways in different cities around the world. The interns will learn about statistical methods used in this research as well as SQL basics. They may also become familiar with working with open-source data maps.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://people.ucsc.edu/~adammb/research.html

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: ENV-04
Title: Extractive Industries, Water Justice, and Social Movements
Primary mentor: James Alejandro Artiga-Purcell
Faculty advisor: Dr. Prof. Jeff Bury
Location: Remote/online
Number of interns: 3

Project description:
Extractive industries underlie many of the world’s most pressing social and environmental challenges. One of the most polluting activities on earth, mining for metals, hydrocarbons, and minerals is a major contributor to global water overuse and pollution. The full impact of extractivism on water must also take into account the myriad social relations with and cultural understandings and experiences of water — as a resource and life source. This research project explores mining’s environmental, social, political economic, and cultural impact on water.

Tasks:
The SIP interns will help with a literature review and analysis of mining’s socio-ecological impacts on water. This task will entail searching for, reading, and organizing academic and other sources regarding mining-water relations.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	OFF	OFF

 

Project code: ENV-05
Title: Understanding Lichens on Redwoods
Primary mentor: Cristina Riani
Faculty advisors: Dr. Prof. Michael Loik, Prof. Elliott Campbell
Location: Remote/online
Number of interns: 4

Project description:
Old-growth redwoods can support huge masses of epiphytes (plants that grow on plants) in their complex canopies. However, many epiphyte species that are common on other trees in the same forests (such as Douglas fir) are not found on redwoods or are much more sparse, especially below the canopy. Epiphytic lichens are important environmental indicators and are sensitive to environmental change. It is particularly important to investigate the relationships between lichens and their host tree species as California forests recover from last year’s fire season. The primary goals of this research project are to compare epiphytic lichen composition between redwood and Douglas fir branches and investigate why some lichens don’t establish on redwoods.

Tasks:
The SIP interns will help survey epiphytic lichens on fallen branches by individually traveling to various forest sites in the Santa Cruz mountains (they will need to live in or near the Bay Area and be able to travel to the sites). They will take pictures of the lichens, which they will later help identify. In the first week, the interns will learn basic background information needed to identify lichens. They will also help collect samples of redwood substrate (wood, bark, and needles) for leachate treatments that will be applied to lichens on collected branches. The interns will need to coordinate with the mentor to take turns bringing samples to Santa Cruz once a week.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	OFF	ON	ON	ON	ON	ON	ON	ON

 

Latin American & Latino Studies

Project code: LAL-01 (ANT)
Title: Immigration and Family Studies — Mixed-Status Family Relationships in Santa Cruz County
Primary mentor: Karina Ruiz
Faculty advisor: Prof. Jessica K. Taft
Location: Remote/online
Number of interns: 3

Project description:
Santa Cruz county has a history of immigration, and primarily agricultural work continues to draw immigrants. But mixed-status families, ones with at least one undocumented and one documented member, are a new phenomena in terms of both legal and family studies. This study aims to understand what family dynamics are like for members of mixed-status families. Drawing on interviews from the We Belong project, this study will bring new analysis to a larger community-initiated and student-led research project.

Tasks:
The SIP interns will learn introductory qualitative analysis. The interns will learn about the grounded theory analytical approach. They will learn about immigrant family experiences through current research and literature. Then, as a team, the SIP interns and mentor will apply these concepts through interview coding, an essential process for qualitative research in the social sciences.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work, lab work

URL: https://webelongproject.sites.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	OFF	OFF

 

Linguistics

Project code: LIN-01
Title: Tone and Stress in Santiago Laxopa Zapotec
Primary mentor: Myke Brinkerhoff
Faculty advisor: Prof. Junko Ito
Location: Remote/online
Number of interns: 3

Project description:
Languages are commonly classified as either being a stressed language or a tonal language. This means that a speaker of will use pitch to convey information about a word. In stressed languages pitch is limited to a specific syllable or portion of the word (i.e., English and Spanish). Tonal languages use varying pitch across a word or a different pitch across each syllable to convey Information about the meaning of the word (i.e., Chinese, Japanese, and Thai). It is commonly believed that languages that have both stress and tone is extremely rare or non-existent across the world’s languages. However, it is commonly claimed that the languages in Mesoamerica are an exception to this typological fact, especially the Zapotecan languages of Oaxaca, Mexico. This project will explore the truth of these claims in an endangered Zapotecan language spoken by approximately 1200 people in Santiago Laxopa, Oaxaca, Mexico and a small number of speakers in Santa Cruz County, CA.

Tasks:
The SIP interns will be asked to assist with annotating and analyzing audio recordings collected from a native speaker of Santiago Laxopa Zapotec. This will consist of them learning: (i) how to segment audio into meaningful parts, (ii) measure meaningful acoustic information, (iii) how to annotate the audio files, and (iv) how to perform statistical analyses on those measurements. Additionally, 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: None
Skills interns will acquire/hone: Field work, lab work, statistical data analysis

URL: http://zapotec.ucsc.edu

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: LIN-02
Title: Investigating Taste and Perspective in Conversation
Primary mentor: Jack Duff
Faculty advisor: Prof. Pranav Anand
Location: Remote/online
Number of interns: 3

Project description:
What do you mean when you say a slice of pizza is “tasty,” a day at the beach was “fun,” or a poem is “beautiful”? And what does it mean when a friend disagrees with you? How do we decide who is right – or can you both be right? Words like “tasty” pose big questions about how humans understand truth and personal experience, questions that are important for researchers who study the structure of meaning in language (semantics). It turns out that with the right type of analysis, we can answer these questions! The goal of this research project will be to carefully examine transcripts and recordings of people having these kinds of arguments, and the ways they are resolved. This kind of detailed investigation will help us learn more about how humans talk about truth and opinions.

Tasks:
The SIP interns will learn how to use scientific tools to study language. Parts of this will involve reading lots of conversations and writing about them. But just because the mentor’s research group studies words doesn’t mean they don’t use numbers! The interns will also use scientific software to investigate those recordings, and write code to design professional graphs. Throughout the internship, the SIP interns will also get to study language generally. The skills the interns will learn will be useful for anyone interested in linguistics, foreign languages, psychology, or computer science. In order to facilitate remote communication and contributions to the project, the SIP interns must each have daily access to a computer with a webcam, a reliable internet connection, and ideally at least two Gb of free memory. They should have the ability to install new programs on this computer (the mentor will train them in the use of programs like Praat, ELAN, and RStudio), and be comfortable sharing their screen for training purposes.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://linguistics.ucsc.edu/about/what-is-linguistics.html

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: LIN-03
Title: Structure of the Korean Nominal Domain
Primary mentor: Nikolas Webster
Faculty advisor: Prof. Ivy Sichel
Location: Remote/online
Number of interns: 3

Project description:
Korean is a language that is well-known to lack definite/indefinite articles (words like “the” and “a/an” in English); the ‘definiteness’ of a given nominal is instead determined by conversational context. And yet, closer investigation of the distribution of Korean demonstratives (words like “this” and “that”) reveals that Korean demonstratives seem to behave perhaps like definite markers in their own right. Given this, the split between article and article-less languages is perhaps not so clear cut as one might predict. The focus of this research project is a re-evaluation of what it means to propose languages ‘lack a determiner category’ and whether the current classifications used to differentiate the syntactic behavior of article and article-less languages are perhaps inaccurate. Korean is the focus language of interest in this project; however, some aspects of the research may include evaluating some data from other languages as well, particularly ones that have also been noted to be article-less.

Tasks:
Interns will assist in finding and sorting relevant research articles, glossing data, preliminary syntactic analysis, and potentially helping with sifting through corpora and linguistic databases with the use of some basic programming. Interns will additionally receive an introduction to the field of linguistics, particularly to the study of syntax, and learn what syntactic data analysis is like and how syntactic research is conducted. Those interested in learning a little bit about Korean nominal structure are especially encouraged to apply. Interns will be taught how to read and romanize Hangeul (the Korean alphabet) as part of the project.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://linguistics.ucsc.edu/about/what-is-linguistics.html

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Molecular, Cell, & Developmental Biology

Project code: MCD-01
Title: Bacteria
Primary mentor: Amanda Carbajal
Faculty advisor: Prof. Manel Camps
Location: Remote/online
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. They threaten human health in the sense of their success of antibiotic resistance superbugs. 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. Their 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. Students will learn to network, collaborate, communicate and see a project through. Interns will learn about a field that is emerging and few, if any other labs are working on.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

URL: https://https://www.metx.ucsc.edu/research/camps.html

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: MCD-02
Title: Development of Tagged Spliceosome Proteins for Purification
Primary mentor: Hannah Maul-Newby
Faculty advisor: Prof. Melissa Jurica
Location: Remote/online
Number of interns: 3

Project description:
The central dogma of biology states that the DNA sequence containing genetic information is copied into messenger RNA, which is then read and translated to generate new proteins. Surprisingly, the DNA sequence of human genes also contains regions that do not hold genetic information. These regions, known as introns, are included in the RNA when it is first made, but are then removed before the information is translated to protein. The removal process is called splicing and is carried out by a molecular machine in the cell called the spliceosome. This research group seeks to understand how the spliceosome assembles upon an intron, including to order the required structural rearrangements of its components. In order to address these questions, the research group utilizes an in vitro assembly assay that relies on HeLa cells to provide the splicing machinery. The research project is to manipulate DNA sequences to engineer “tagged” spliceosome components. These tagged-spliceosomal proteins will then be utilized to purify spliceosome complexes.

Tasks:
The SIP interns will obtain a basic understanding of splicing, as well as learn basic DNA cloning techniques. Together, the interns will gain an appreciation for how standard techniques are still unlocking basic questions about fundamental processes. The interns will choose an early complex spliceosome protein of interest and design a cloning strategy that the mentor will perform. Specifically, the SIP intern will: (1) learn how to use the spliceosome database and will choose a protein of interest; (2) learn how to utilize a DNA sequence editing tool; (3) design primers and a cloning strategy to engineer a tag into the protein; (4) perform data analysis of results as provided by the mentor; (5) learn how to troubleshoot as required, based on the obtained data; (6) read primary papers from the field; and (7) attend weekly lab meetings with the entire lab. An overarching goal is for the SIP interns to develop an understanding of the logic behind the experiments, and how this work will contribute to the larger body of research.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work

URL: https://bio.research.ucsc.edu/people/jurica/index.html

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	OFF	ON	ON

 

Project code: MCD-03
Title: What do Neurons Say? Decoding the Brain with Statistical and Computational Methods
Primary mentor: Yufei Si
Faculty advisor: Prof. David Feldheim
Location: Remote/online
Number of interns: 3

Project description:
“If the human brain were so simple that we could understand it, we would be so simple that we couldn’t.” Yet, neuroscientists are making significant progress in understanding the brain, and one of the first steps is to decode the neuronal code that our brain uses. We now know that neurons use electric signals as their language to communicate, and these signals can be recorded using in vivo electrophysiology techniques. However, how do we know what these neurons are talking about with their electric signals? The SIP mentor and interns will find out using statistical and computational methods.

Tasks:
The SIP interns will gain a basic understanding of the nervous system, learn about basic ideas of how to study the brain using available techniques, and practice basic computational analysis with existing electrophysiology data. Specifically, the SIP interns will take part in the following: (1) reading primary papers/textbooks from the field and understanding some general concepts of neuroscience; (2) understanding the logic behind the mentor’s project and experiments being performed; (3) learning about basic statistical and computational tools and understanding the analytical methods being used; (4) analyzing existing data as a final practice/project.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://feldheimlab.mcdb.ucsc.edu/index.html

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	OFF	ON	ON	ON	ON

 

Project code: MCD-04
Title: Identification of Novel cis-Regulatory Elements at the Nkx3.1 Gene Locus
Primary mentor: Dr. Qing Xie
Faculty advisor: Prof. Zhu Wang
Location: Remote/online
Number of interns: 3

Project description:
Gene expression is precisely controlled in developmental, physiological and pathological processes. At transcriptional level, gene expression is regulated by the integrated action of many small segments of genomic DNA, called cis-regulatory elements. One of the projects in the laboratory is to study the molecular mechanism of transcription regulation of the Nkx3.1, a critical gene for maintaining prostate cell fate and suppressing tumor initiation. SIP interns will take the advantage of the established sequence databases and a bunch of sequence analyzing softwares to intensively examine the DNA sequence at the Nkx3.1 locus and predict the potential cis-regulatory elements.

Tasks:
The SIP interns will be guided to study particular parts of Biology 101 and get more comprehensive knowledge of the central dogma. After understanding the concepts of transcription, translation, enhancer, promoter, transcription factor, exon, intron, coding sequence, and UTRs, interns will study to use the UCSC Genome Browser, the JASPAR transcription factor binding profile database and the MEME Motif-based sequence analysis tools. At the end, interns will do the in silicon analysis of the 17 Kb DNA sequence at the Nxk3.1 gene locus to identify binding sites for several important transcription factors in prostate biology.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Statistical data analysis

URL: https://wanglab.ucsc.edu/research/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	OFF	ON	ON	OFF	ON	ON	OFF	ON

 

Project code: MCD-05
Title: Engineering Affinity Tagged Spliceosome Proteins
Primary mentor: Angela Amorello
Faculty advisor: Prof. Melissa Jurica
Location: Remote/online
Number of interns: 3

Project description:
Gene expression occurs when DNA is transcribed into messenger RNA (mRNA), followed by translation of mRNA into proteins that go on to carry out biological processes. To ensure proteins are properly made, gene expression must be tightly regulated. One way eukaryotes accomplish this is by transcribing RNA with intron sequences that interrupt the exon sequences that encode proteins. Therefore, protein cannot be produced until the introns are removed and the exons are joined together in a process called splicing. Splicing is catalyzed by a large RNA and protein complex called the spliceosome. The focus of the mentor’s lab is to understand early recognition of intron sequences by spliceosome components. To study this process, the lab utilizes an in vitro spliceosome assembly system which uses HeLa cell extracts. This research project entails engineering an affinity tag on a spliceosome associated helicase to be used for probing protein-protein interactions.

Tasks:
The SIP interns will: (1) gain a general understanding of splicing; (2) learn how to design plasmids; (3) learn how to use bioinformatic tools like BLAST; (4) read splicing-related journal articles; (5) learn how to analyze data; and (6) attend weekly lab meetings. The goal is for the SIP interns to gain critical thinking and problem-solving skills as it pertains to this particular subject area and scientific research in general.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work, statistical data analysis

URL: https://bio.research.ucsc.edu/people/jurica/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	OFF	ON	ON	ON	ON	OFF	ON

 

Ocean Sciences

Project code: OCS-01
Title: Marine Mammal Physiology — Pinniped Heart Rate Study
Primary mentor: Ryan Jones
Faculty advisor: Dr. Colleen Reichmuth
Location: Remote/online
Number of interns: 3

Project description:
This research lab explores the inner worlds of amphibious marine mammals. Observations and experiments conducted with trained animals in our laboratory allow us to examine the perceptual and cognitive mechanisms that enable individuals to gather, organize, and use various types of information, and the physiological mechanisms that support behavioral plasticity. Observations made in the field allow us to see how perception and cognition are translated into decisions and actions. Comparative studies in both settings help us to understand how ecological, evolutionary, and life history factors have influenced different marine mammal species. This project aims to classify and compare resting cardiorespiratory behavior of up to 9 species of pinnipeds (seals, sea lions, and walruses). Data are collected using non-invasive, electrophysiological techniques with trained, cooperating subjects.

Tasks:
The SIP interns will assist with remote data analysis by scoring respiratory behavior as well as by maintaining and updating an existing database.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

URL: https://pinnipedlab.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

 

Project code: OCS-03
Title: Marine Mammal Physiology: Growth and Haul Out Patterns of Alaskan Ice Seals
Primary mentor: Madilyn Pardini
Faculty advisor: Dr. Colleen Reichmuth
Location: Remote/online
Number of interns: 3

Project description:
Nowhere on Earth are the effects of climate change more apparent than in the Arctic. Ice-dependent Arctic and sub-Arctic seals, including ringed (Pusa hispida), bearded (Erignathus barbatus), and spotted (Phoca largha) seals, are important high trophic-level predators that exert top-down control within these ecosystems. Unfortunately, relatively little is known about their basic biology and physiology, leaving management agencies and conservation practitioners with an incomplete understanding of the physiological requirements and limitations of these species, and a weak ability to make predictions about the capacity of ice-dependent seals to respond to rapid environmental change. It is tough to collect physiological data from ice-dependent seals in the wild, which makes information gained from captive individuals vital to the conservation and management of these species. The aim of this project is to work with and study the largest collection of trained ice-dependent seals in the world, in order to obtain valuable information about the biology and physiology of these unique and important species. This research lab collects longitudinal data from the seals in our care to examine health parameters, determine short- and long-term energetic requirements, define thermal strategies and limitations, and describe the molting physiology of each species.

Tasks:
The SIP interns will be exposed to various data collection methods used in a managed care research setting and will learn how data collected with trained animals in a laboratory can help to inform policy. The interns will: (1) be given relevant primary literature to read and discuss; (2) learn to use photo analysis software to track growth; (3) analyze video data and record behavioral patterns; and (4) carry out other assignments and projects as assigned.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work, statistical data analysis

URL: http://pinnipedlab.ucsc.edu

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Physics

Project code: PHY-01
Title: Multi-Physics Electro-Thermal Simulation of Memristors
Primary mentor: Ali Fares
Faculty advisor: Prof. Nobuhiko Kobayashi
Location: Remote/online
Number of interns: 3

Project description:
In this project, we will develop a mathematical model to run two physics simulations of memristors, namely thermal and electric conductivity of the devices, which will be implemented via a parallel computing framework, where two separate subprograms controlled by a main program will solve each equation separately and compare results at the end. Memristors, or memory resistors, are resistors whose resistance is based on their voltage history, which enables them to store memory in the form of a variable resistance. They have use in a multitude of fields, namely in the form of programmable memory as well as in the creation of artificial neural networks, where the ability for the memristors resistance to change based on history of voltage and current application can be used to form logic circuits that can “remember” previous interactions, similar to neurons in the brain.

Tasks:
SIP Interns will: (1) be provided the equations used to model thermal and electrical properties of memory resistors and will be taught by the mentor what they are describing; (2) be guided through the process of transforming the equations into a form solvable in Python; (3) use the Python libraries ODEINT and GEKKO to solve the equations and get results on the properties of the device; (4) discuss the results and the implications that it has for future research into the thermal and electrical properties of memory resistors. Students should be comfortable programming in a high level programming language, such as Python, and have a decent understanding of some fundamental college math, such as calculus, though most advanced topics, such as differential equations and math models the students will be guided through by the mentor.

Required skills for interns prior to acceptance: Computer programming, lab work, statistical analysis
Skills interns will acquire/hone: Computer programming, lab work, statistical analysis

URL: https://nectar.soe.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PHY-02
Title: Optimizing Protective Silver Mirror Coating to Improve Reflectivity in the Short Wavelength Range
Primary mentor: Soren Tornoe
Faculty advisor: Prof. Nobuhiko Kobayashi
Location: Remote/online
Number of interns: 3

Project description:
Silver mirrors are excellent for the creation of high-quality telescopes and deep space observation but suffer from severe environmental degradation requiring a protective coating. This thin coating effects how light interacts with the mirror and can be especially problematic for short wavelengths of light. As such, the primary goal of this project for the summer is to effectively model and optimize the optical properties of silver mirrors with protective coatings on them.

Tasks:
The SIP interns will model and optimize the optical properties of coated silver mirrors by writing code using a programming language like MATLAB 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.

Required skills for interns prior to acceptance: Computer programming
Skills interns will acquire/hone: Computer programming, lab work

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PHY-03
Title: Optical Properties of Cu-AlOx Nanocomposites
Primary mentor: Greyson Shoop
Faculty advisor: Prof. Nobuhiko Kobayashi
Location: Remote/online
Number of interns: 3

Project description:
Thin film structures are being researched for a variety of reasons including the ability of changing the chemical or physical properties of materials. One of these properties of importance are the optical properties of thin film materials at the nano scale, how light interacts with these thin film structures. The nanocomposite structure of interest is Cu-AlOx which is a metal-oxide thin film layer which requires precise methods for fabrication. Among the many methods of creating thin films at the nano scale are Atomic Layer Deposition (ALD) and Magnetron Sputtering (SPU) which allows the creation of these nanometer thick thin films of different materials layered on top of one another. These deposition methods allow the fabrication of thin film structures that are hundreds of layers thick but at nano scale thickness. Computational methods are of interest in order to simulate the optical properties of potential thin film structures without having to construct them and perform in person diagnostics.

Tasks:
Interns will learn of the irregularities of nano scale materials and the various deposition methods for thin film characterization. Interns will utilize the transfer matrix method to simulate the spectral reflectivity of the materials in question in order to understand optical properties of Cu-AlOx nanocomposite thin films.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Psychology

Project code: PSY-01
Title: Reciprocity in Conversation
Primary mentor: Andrew Guydish
Faculty advisor: Prof. Jean E. Fox Tree
Location: Remote/online
Number of interns: 3

Project description:
Do people work together to create reciprocal balances across conversations? The SIP mentor is interested in conversational dynamics and how people carry and maintain conversations. In particular, the mentor is interested in conversational balance between participants throughout the course of the conversation, and how these balances influence how individuals communicate with one another.

Tasks:
The SIP interns will work on numerous aspects of development regarding psychological experiments. The interns will work with the mentor in the development of experiments examining areas of interest pertaining to cognitive psychology (e.g., discussing experimental design, conducting literature reviews on related concepts), work with real data (e.g., transcribing videos, examining transcripts), as well as running participants in psychological experiments under supervision. Through this process, the SIP interns will gain experience in the following: writing APA style annotated bibliographies; processes associated with experimental development; running human participants; analyzing real data in IBM’s SPSS; and development and use of Python algorithms for data parsing and analysis.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work, statistical data analysis

URL: https://guydish.sites.ucsc.edu, https://foxtree.sites.ucsc.edu

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	OFF	ON	ON	ON	ON	OFF

 

Project code: PSY-02
Title: Earworms
Primary mentor: Matt Evans
Faculty advisor: Prof. Nicolas Davidenko
Location: Remote/online
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 mentor and SIP interns will design and implement an experiment using behavioral techniques that will help contribute to the scientific understanding of various aspects of this near-ubiquitous human experience. This project will specifically explore the invasiveness of primed INMI when the participant is intentionally holding different musical imagery in mind.

Tasks:
The SIP interns will participate in the full process of designing an experiment, from literature review through pilot data collection and preliminary data analysis. Interns will read scientific articles on a range of topics (such as musical imagery and mind wandering) and discuss them as a group with the mentor to help refine the research question. Interns will then work with the mentor to build the experiment using Matlab, collect pilot data, and perform statistical analyses. Interns can expect to learn programming skills, gain insight into and experience with the complete process of experimental design, and practice performing and interpreting statistical analyses.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

 

Project code: PSY-05
Title: Correctional Officer Abuse of Power
Primary mentor: Jade Moore
Faculty advisor: Prof. Craig Haney
Location: Remote/online
Number of interns: 3

Project description:
The SIP interns will be investigating how correctional officers’ abuse of power may be impacting Black individuals in prison. Black individuals have historically been discriminated against in many areas of the U.S.’s criminal justice system (policing, sentencing, etc.). The SIP interns will be analyzing different media outlet reports (newspapers, broadcasts, etc.) to investigate how this discriminatory treatment may translate over in correctional institutions. The goals will be to try to establish if Black individuals are more often the targets of force in correctional settings and what kind of information the media has access to when investigating reports of correctional officers’ abuse of force.

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
Skills interns will acquire/hone: Lab work, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	OFF	ON	ON

 

Project code: PSY-06
Title: Criminal Justice in the Media
Primary mentor: Jada Cheek
Faculty advisor: Prof. Craig Haney
Location: Remote/online
Number of interns: 3

Project description:
Dehumanization of African Americans throughout history has been salient since the inception of the U.S. Dehumanization is the phenomena of seeing a person or group of people as less than human or animal-like. This can lead to discrimination, violence, and even fatal encounters with dehumanized groups. Police brutality against African Americans is a huge issue in the U.S. Dehumanization is just one factor contributing to police violence against Black people. This project will be analyzing the media coverage on the Breonna Taylor and George Floyd murders. The research group will investigate the role of dehumanizing language in the media coverage of these cases, and also look at the differences in the descriptions of Breonna Taylor (a Black woman) vs. George Floyd (a Black man) to analyze for gender differences, as well.

Tasks:
The interns will do background readings surrounding the psychological phenomenon of dehumanization and media criminology that will contribute to the literature review of the study. They will help to code newspaper articles and live news transcripts that cover the Breonna Taylor and George Floyd cases, and run and analyze statistical analyses.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	OFF	ON	ON	ON

 

 

Project code: PSY-08
Title: Spontaneous Politeness
Primary mentor: Elise Duffau
Faculty advisor: Prof. Jean E. Fox Tree
Location: Remote/online
Number of interns: 4

Project description:
The SIP mentor is interested in expanding on how we communicate politeness with artificial agents. To explore this, a detailed understanding of how people spontaneously use politeness must be examined. The current project will examine how people use different politeness strategies in different settings and how those strategies may or may not be applied to artificial agent communications.

Tasks:
Interns will gain experience in the various aspects of psychological experiments. Interns will work with the mentor in learning how to conduct research in cognitive psychology related to the area of interest. Research skills interns will learn and use include: learning how to design experiments and being part of designing experiments this summer; conducting literature reviews; learning how to code data, and then coding data; and analyzing data in SPSS, R or Python. Interns will also gain experience in writing APA format annotated bibliographies.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work, statistical data analysis

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-09
Title: Mind-Controlled Illusory Apparent Motion
Primary mentor: Allison Allen
Faculty advisor: Prof. Nicolas Davidenko
Location: Remote/online
Number of interns: 3

Project description:
Why do we experience illusions? For psychologists, studying illusions helps to reveal some of the properties and quirks of perception. One such illusion is Illusory Apparent Motion (IAM) where ambiguous apparent motion is elicited by randomly refreshing pixel textures. Previous research using other apparent motion illusions has found that motion ambiguity can be controlled mentally (for example, one can mentally will ambiguous motion to appear in a clockwise, as opposed to a counterclockwise, direction). This research project explores how IAM is similarly susceptible to mental control in different contexts, and the group is running and designing experiments to measure this in the lab.

Tasks:
Interns will have the opportunity to learn about a variety of illusions and what each illusion reveals about the nature of the human sensory system. This will be done by reading scientific articles each week and discussing them with the mentor. The interns will also gain hands on experience running participants (supervised) in a laboratory experiment and will learn how to program and analyze data using Matlab.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

URL: http://davidenko.sites.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	OFF	ON	ON	ON	ON	ON	ON

 

Project code: PSY-10
Title: Children’s Learning through Collaboration
Primary mentor: Samantha Basch
Faculty advisor: Prof. Su-hua Wang
Location: Remote/online
Number of interns: 3

Project description:
The mentor’s research focuses on how toddlers and preschoolers learn through collaboration. This summer, the mentor’s research team will study parent-child collaboration during play. The team will study both natural play and structured play, with a special focus on parental question-asking. The hope is the results will shed light on how culture and context shape parent-child collaboration and learning. Interns will also have the opportunity to design their own research proposal in the area of Developmental Psychology.

Tasks:
The SIP interns will get experience with the full range of activities that occur in a developmental psychology lab, including scheduling, explaining informed consent, and running experiments. The interns will also learn how to write a project proposal, collect and analyze observational data. These are important skills for any psychologist. Finally, the interns will have the chance to work with other members of the Infant and Child Development Lab on ongoing projects.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work, statistical data analysis

URL: https://suhua.sites.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-11
Title: Researcher Identity and Bias — How Psychology Researchers use “Positionality Statements” in Published Articles to Reflect on the Influence of Their Social Position, Identity, and Bias During Research
Primary mentor: Daniel Copulsky
Faculty advisor: Prof. Phillip Hammack
Location: Remote/online
Number of interns: 3

Project description:
Our individual life experiences shape the kind of scientific questions we ask, the way we conduct our research studies, and the way we interpret the results. As social science researchers, we are called on to be reflective about how our own identities can influence and bias our work. “Positionality” is the way that our social positions (like gender, race, and sexual orientation) shape the way we see the world. “Reflexivity” is the process we use to examine how these perspectives shape the research we do, often as an insider or outsider of groups that we do research about. Scholarly articles sometimes include a statement from the authors about their identity, positionality, or reflexivity process. This project studies the use of these “positionality statements” in recently published articles from psychology journals, considering both how common they are and their common themes.

Tasks:
Interns will do background reading about research methods in psychology, processes for practicing reflexivity, and the use of positionality statements in journal articles. The research team will work together to develop a method for finding positionality statements in recently published psychology journal articles. Interns will read positionality statements closely, using qualitative analysis methods to identify themes across the statements and to categorize common elements of the texts. Quantitative analysis will be used to measure how common these elements are. The research team will meet daily over Zoom to review readings, project progress, and tasks for the day.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Statistical data analysis

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-12
Title: Exploring Everyday Helping
Primary mentor: Margie Martinez
Faculty advisor: Prof. Audun Dahl
Location: Remote/online
Number of interns: 3

Project description:
How do we come to help others? The mentor’s research group examines moral reasoning in relation to one’s actions in everyday contexts. The group is particularly interested in how parent-child interactions influence the development of helping behavior and how this may vary across different cultural backgrounds. This research project will examine how the daily routines of families impact judgments, reasoning, and decisions about helping behaviors. By examining the everyday experiences with helping, the interns and mentor can gain a better understanding of how children and adults come to the moral decision of who and when to help.

Tasks:
The SIP interns will be involved in most or all aspects of this research project. The interns may help design research studies, collect data (for instance, through interviews), analyze video recordings or interview transcripts, and/or discuss research articles. The interns may work with data from past or current projects exploring how children and young adults think about helping. The research group will discuss literature relevant to the project and moral development. This research project will provide an opportunity for interns to learn about and contribute to all stages of psychological research.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work, statistical data analysis

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	OFF	ON	ON	OFF	ON	ON

 

Project code: PSY-13
Title: Service-Learning Outcomes of College Students
Primary mentor: Miguel Lopezzi
Faculty advisor: Prof. Regina Langhout
Location: Remote/online
Number of interns: 4

Project description:
Service-learning classes are important because they help students learn while they are also engaged in the community and giving back. But, not all service-learning courses are the same. Yet, they are often treated the same in the research literature. In this research project, the SIP mentor and interns will work together to figure out differences in the quality of the course design across several service-learning courses to see if these differences help them to understand college student outcomes better. For example, is the quality of the service-learning course design (course materials [e.g., syllabus]) related to certain kinds of civic outcomes (diverse citizenship [e.g., students’ openness to others and their willingness and desire to be agents of change])?

Tasks:
The SIP interns will listen to and transcribe (write down or type out), word for word, interviews between the graduate student researcher and professors who teach service-learning classes. The interns will also check the transcriptions for accuracy, and help to categorize the interviews to determine the quality and nature of the service-learning classes. The SIP interns will learn a lot about interviews, how to work with word data, and the quality aspects of service-learning courses. The interns will get to help make important decisions about the quality of the courses.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-14
Title: Neural Mechanisms of Perceptual Decision Making
Primary mentor: Wei Dou
Faculty advisor: Prof. Jason Samaha
Location: Remote/online
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 the 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:
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. 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: None
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

URL: https://samahalab.ucsc.edu/

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-15
Title: Brain Activity Underlying Visual Perception
Primary mentor: Audrey Morrow
Faculty advisor: Prof. Jason Samaha
Location: Remote/online
Number of interns: 3

Project description:
This research 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 alpha waves and stimulus-locked event-related potentials (ERPs) from brain areas associated with vision. Alpha power and ERP amplitudes change during visual perception and are associated with changes in performance on perceptual tasks that use stimuli that are difficult to distinguish. The interns will gain an understanding of how these neural patterns are analyzed and what those analyses can tell us about brain activity when we attend to and perceive visual information.

Tasks:
The SIP interns on this research project will learn about brain activity underlying attention and perception, and will learn how to organize, analyze, and visualize EEG data by programming in Matlab. The interns will learn about paradigms and techniques used in cognitive neuroscience studies and may help to program new studies that use perceptual detection or discrimination tasks.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis

URL: https://samahalab.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-16
Title: Online Searching, Memory, and Metacognition
Primary mentor: Dana-Lis Bittner
Faculty advisor: Prof. Benjamin Storm
Location: Remote/online
Number of interns: 3

Project description:
The internet is a vast and ever-growing source of information and we have come to rely on it more and more as an external memory store in recent years. The mentor is cognizant of the immense benefits that come with having access to all of this information at our fingertips, but wishes to explore potential negative or unwanted impacts of being able to look up information online that easily on our cognition and behavior. Some of the questions that are being explored in the mentor’s lab are “Do we grow dependent on the internet?”, “Does online searching change how we behave or think or assess our own knowledge?”, or “How does prior knowledge change how or whether we search for information online?”. More specifically, this summer, the mentor would like to investigate whether remembering with the internet (using the internet to jog your memory) could actually lead to a phenomenon referred to as “collaborative inhibition”, resulting in someone remembering less of the originally learned material. The mentor feels that the dynamic nature of online search engines and their use in everyday settings, such as work and education, makes for an exciting and highly relevant field of study.

Tasks:
The SIP interns will help develop a new research project, as well as potentially work on ongoing research projects. Throughout the process, the interns will develop a conceptual understanding of research within cognitive psychology through hands-on experience with various tasks required to run an experiment. They will delve into the existing literature regarding the internet and online searching as well as its impacts on human cognition and behavior. Interns will also actively be involved in the conceptualization of a new study and the generation of stimulus materials. They will also gain experience with constructing an online survey and coding its logical flow, as well as potentially help build unique websites needed for a study. To gain experience with data cleaning and analysis, the SIP interns will work with data from past and possibly current projects that explore the impact of online searching on behavior, memory, and metacognition. The interns and mentor will discuss literature, theory, implications of predicted findings, ethical considerations about research more generally, and research tasks. This research project provides a great opportunity for the interns to learn about psychological research at every single stage — from reviewing the existing literature, over conceptualizing a new study, to analyzing and interpreting results.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Computer programming, statistical data analysis, writing literature reviews in APA format, working with software commonly used in psychological research (e.g., Qualtrics, Excel, SPSS, and R)

URL: https://people.ucsc.edu/~bcstorm/research.html

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-17
Title: Getting Students Excited About Research: Implementing Social Justice and Communal Values in Research to Motivate Student Interest and Success
Primary mentor: Katherine Quinteros
Faculty advisor: Prof. Rebecca Covarrubias
Location: Remote/online
Number of interns: 3

Project description:
Science and research fields are often perceived as being sterile and detached from the everyday lives of people. This perception often causes students to leave science fields early on in higher education, particularly racially minoritized students. For this research project, the mentor is interested in whether integrating communal values (e.g., helping each other) and social justice values (e.g., transforming systems) into research assistant descriptions can impact how students perceive the research project. The mentor is also interested in testing differences among racial and ethnic groups to understand which students are benefitted and in what ways.

Tasks:
The SIP interns will learn how to: (1) conduct a literature review of scholarly articles related to the project; (2) create an annotated bibliography; (3) develop research questions and hypotheses; (4) design an experiment and survey; and (5) analyze pilot data using SPSS.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Statistical data analysis

URL: https://rcovarrubias.sites.ucsc.edu

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	OFF	ON	ON	OFF

 

Project code: PSY-18
Title: Why do Students Cheat?
Primary mentor: Fiona Debernardi
Faculty advisor: Prof. Audun Dahl
Secondary mentor: Talia Waltzer
Location: Remote/online
Number of interns: 4

Project description:
This research project examines ethical decision-making in academic settings, specifically focusing on students’ decisions to cheat. The SIP interns will help review literature on academic integrity, and assist with documenting and analyzing integrity policies from a wide sample of colleges across the US. The first of its kind in the US, this research project will advance psychological knowledge on cheating by describing theoretical viewpoints of cheating, students’ motives for cheating, strategies for prevention, and whether these insights are actually applied in real schools’ policies. The interns will also assist with analyzing data from real academic misconduct cases at UCSC, advancing our understanding of the contexts that lead students to cheat.

Tasks:
To learn more about moral decision making and academic integrity, the SIP interns will assist with literature review, data collection, classifying open-ended data, and data analysis (using spreadsheets) for lab projects focusing on academic integrity. The interns may also assist with organizing and interpreting qualitative and quantitative data from college records. These tasks will involve reading published research papers, academic policies, and sensitive narrative accounts of student experiences with cheating. In addition, the SIP interns may help with website design. The work 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
Skills interns will acquire/hone: Computer programming, lab work, statistical data analysis

URL: https://aop.ucsc.edu/

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-19
Title: Social Presence in Online Learning
Primary mentor: Yasmin Chowdhury
Faculty advisor: Prof. Jean E. Fox Tree
Location: Remote/online
Number of interns: 3

Project description:
With everything being online, it is important to look into computer-mediated interactions and how they differ from in-person interactions. In this research project, the SIP interns and mentor are going to look at social presence in different settings (chat, audio, video) to see how they differ based on different media. Social presence is how physically present a person feels their conversational partner is when interacting with them via different media. The mentor’s research group is particularly interested in seeing if group sizes, level of familiarity, and other factors impact social presence.

Tasks:
The SIP interns will read research papers, complete literature reviews, code data, run experimental participants (with supervision), and transcribe interactions. The interns will have bi-weekly meetings with research teams where they will discuss ongoing and upcoming work.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work, statistical data analysis

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-20
Title: Talking, Texting, and Emotions
Primary mentor: Vanessa Oviedo
Faculty advisor: Prof. Jean E. Fox Tree
Location: Remote/online
Number of interns: 3

Project description:
The mentor’s research interests are in technology assisted communication and modality switching. Specifically, the mentor is interested in the way that people communicate and perceive their interactions when they switch between two communication mediums, such as from text messaging to audio. The current research project is examining differences in emotional communication when people interact via messaging and audio.

Tasks:
The SIP interns will work with the mentor in the completion of experiments by reviewing experimental design, conducting APA style literature reviews, and completing APA style annotated bibliographies. The interns will also work with real data in which they will transcribe audio files, examine transcripts, enter and clean quantitative data using SPSS, and code qualitative audio files. In working with the mentor, the SIP interns will learn skills such as designing a research study, completing a literature review, creating research questions and developing hypotheses, entering quantitative and qualitative data, conducting a corpora analysis, and analyzing the final data set.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Lab work, statistical data analysis

URL: https://foxtree.sites.ucsc.edu

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	ON	ON	ON	ON	ON

 

Project code: PSY-21
Title: First Generation College Students
Primary mentor: Andrew Takimoto
Faculty advisor: Prof. Margarita Azmitia
Location: Remote/online
Number of interns: 3

Project description:
For students who are the first in their families to go to college (first gen students), going to college can be both exciting and stressful. First gen college students can find it difficult to make new friends on campus because they feel stressed that their peers often know more about college than they do. First gen students can also lack the confidence that they will do well in college and graduate. This research project will use survey data collected from first gen students at UCSC to find out if social support (or the lack of it) can help first gen students feel confident that they will do well in college, find a major they feel passionate about, and graduate.

Tasks:
The SIP interns will learn to read research articles critically and search for additional articles online and at the UCSC library. The interns will also learn to write an introduction to a research paper using the writing conventions in psychology. The interns will develop hypotheses to test about the role of social support and self-confidence in succeeding in college and will use survey data collected from first gen students attending UCSC to test them. Finally, the SIP interns will develop a presentation of their research project that they will practice in the research group and deliver at the SIP conference at the end of the summer.

Required skills for interns prior to acceptance: Lab work, statistical data analysis
Skills interns will acquire/hone: Lab work, statistical data analysis

Special age requirement: Interns must be 16 years old by June 21, 2021.

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	OFF	ON	ON	ON	ON	OFF	ON	ON

 

Sociology

Project code: SOC-01
Title: College Education, Gender, and Sexuality
Primary mentor: Michelle Parra
Faculty advisor: Prof. Julie Bettie
Location: Remote/online
Number of interns: 3

Project description:
How does attending college shape girls’ gender and sexual behaviors? Previous research has found that attending college can immerse white girls in cultural contexts where they can experience new gender and sexual freedoms. Little research has examined how pursuing a four-year college degree shapes the ways in which girls of color view their gender and sexualities. This research project utilizes sociology, feminist studies, and ethnic studies to examine the experiences of girls of color within university settings with a particular focus on first-generation Latina college students. The mentor’s research describes the various ways that attending college results in new gender and sexual oppressions and freedoms for Latina college students.

Tasks:
The SIP interns will have the opportunity to read literature on gender, sexuality, and education. They will learn how to retrieve scholarly journals and write research summaries (annotations). In addition, the interns will assist the mentor with reviewing (coding) interview data. The interns will also have the opportunity to create a research presentation based on the literature that they read and the interviews that they coded. They can present their research findings in an undergraduate Sexualities course that the mentor is teaching this summer.

Required skills for interns prior to acceptance: None
Skills interns will acquire/hone: Field work

Program week number:	1	2	3	4	5	6	7	8
Mentor’s availability:	ON	ON	ON	OFF	ON	ON	ON	ON