2025 Research Projects – The Science Internship Program (SIP)

Applied Artificial Intelligence (AAI)

AAI-01: Autoencoders in Space Optical Communications

Primary Mentor: Abdulaziz Alatawi (he/him)

Number of Interns: 3

Project Description: Autoencoders are neural networks that can learn a compressed representation of the input data, called the latent code, through unsupervised learning. This code is a summary or compression of the input that can be used for a variety of tasks, such as image generation, anomaly detection, and dimensionality reduction. This research project focuses on autoencoders. The SIP interns will use Python libraries like PyTorch and TensorFlow to study research papers and reproduce results. This will help the interns gain practical experience in implementing end-to-end performance systems in wireless communication systems and understand other applications of autoencoders. Additionally, the interns will receive a good introduction to the Python programming language and space optical wireless communications. The SIP interns will periodically present their progress to ensure a good learning process.

Tasks: To start, the SIP interns will receive a specific schedule for the first two weeks to learn Python programming. The coursework will entail completing exercises, watching videos, and receiving a comprehensive introduction to wireless communications. Additionally, the interns will be asked to submit daily progress reports on their assigned tasks. The interns will also be required to read the mentors’ published GLOBECOM paper to understand the system model right from the beginning. Starting in week #3, the SIP interns will be taught how to implement autoencoders in wireless communications and create plots for (Bit Error Rate) BER results and constellation diagrams presented in the GLOBECOM paper. Through reading technical papers, the interns will focus on improving the published research work by introducing security constraints and improving BER results compared to state-of-the-art models. In addition, the interns will explore different fading channel scenarios and develop a system that can function effectively not only in specific channel conditions but also in various channel scenarios. Additionally, it would be valuable to compare the proposed autoencoder solutions for various channel conditions with the federated learning approach.

Arts, Culture, and STEM (ACS)

ACS-01: Graphic Research: Visual Approaches for the Humanities, Social Sciences, and Environmental Studies

Primary Mentor: Rachel (Raty) Syka (they/them/she/her)

Number of Interns: 5

Project Description: This research project investigates visual approaches to archival and field-based research in the humanities, social sciences, and environmental studies. As a part of my greater research about the role of illustration, comics, drawing, print media, and alternative photography in anthropology, agriculture, and environmental studies, I invite student interns to pursue a project of their own design through experimental visual means. Interns will build skills in archival and library-based research, field interview methods, and independent research design through mentorship throughout the summer course. Together we will investigate methods of approaching questions visually through a variety of media, suggesting modes of communication that extend beyond the written word. This project is a great fit for students interested in the arts, humanities, sociology, psychology, anthropology, and the environment.

Tasks:

Library-based research
Archival research
Image analysis
Writing
Peer feedback & critique
Visual design in a medium of their choosing

Astronomy and Astrophysics (AST)

AST-01: Identifying Variable Stars in the Andromeda Galaxy: Color-Color Analysis and Comparison of Spectroscopy and Photometry

Primary Mentor: Avi Patel (he/him)

Number of Interns: 3

Project Description: The Andromeda galaxy (M31) offers a global perspective of resolved stellar populations and is an ideal laboratory for studying stellar evolution. As stars evolve, they undergo changes in brightness over time for various reasons (mass loss from a companion, supernova explosion, instabilities/pulsation). The Panchromatic Hubble Andromeda Treasury (PHAT) survey contains measurements of roughly 117 million stars spanning one-third of M31‚Äôs disk and is a treasure trove for discovery and analysis of variable stars. The mentor‚Äôs group is working on developing two novel techniques for identifying variable stars: The first uses the stars‚Äô color (difference in brightness between two filters) to assess their variability. The stars‚Äô brightness measurements in different filters were recorded at different times, so variable stars should deviate from the tight locus formed by non-variable stars in color-color space. Furthermore, thanks to the SPLASH survey, we have Keck DEIMOS spectra for a subset of stars in PHAT. The second approach is to search for large offsets between the brightness measurements of the DEIMOS spectra and the PHAT photometry, since these are attributed to stellar variability.

Tasks: The SIP interns will first work on identifying variable stars using difference images taken from the overlapping fields in the PHAT survey footprint. Then, using this sample of variable stars as a training set, they will develop software to investigate novel ways to identify variable stars from the PHAT survey. Some of the interns will examine their variable stars‚Äô location in color-color space. Others will work on cross matching their variable stars‚Äô to Keck DEIMOS spectroscopic data from SPLASH to look for brightness offsets against the PHAT photometry.

URL: https://app.ubinum.com/lab/raja-uco-lick-observatory/research

AST-02: Milky Way Stellar Halo Star Detection

Primary Mentor: Abbie Baddeley (she/her) & Dalya Gregorio Chas (she/her)

Number of Interns: 3

Project Description: Using advanced computational techniques, we analyze data from telescopes that identify star groups, which helps us better understand our galaxy and its history. Our research and team effort contribute to exploring how the Milky Way was formed and has evolved. This project doesn’t just give us a deeper understanding of our stars but also of our galaxies’ history and formation.

Tasks: Interns will be asked to help with data analysis by creating graphs, plots, and charts through Python. There are Python tutorials available for all levels of skill. They will have a chance to learn about specific methods used in astrophysics to interpret the data we receive from telescope images of space. Interns will spend their time working as a group with their mentor(s), working as a group without their mentor(s), and working individually. They will have some supplemental reading that will help them better understand the context within which this project is occurring and why we are interested in it. Although it is listed below, there will be no lab work involved. The project will focus on computer programming and data analysis.

URL: https://scholar.google.com/citations?user=QmZ1BzcAAAAJ&hl=en

AST-03: Stellar Population Analysis of the Inner Dynamically Hot Component in M33 Using Keck/DEIMOS TREX Survey Data *TSIP

Primary Mentor: Gautam Kumaran (he/him)

Number of Interns: 3

Project Description: Our project explores the Triangulum Galaxy (M33) using spectroscopic data from the Keck DEIMOS telescope as part of the TREX survey. By analyzing the motion of stars in M33’s inner regions, we aim to uncover how its dynamically hot stellar component—a group of stars that move differently from the main disk—formed and evolved. We’ll classify stars by age and fit advanced models to their velocities, revealing hidden structures like a non-rotating spheroid and a lagging disk. This helps us piece together the story of how galaxies like M33 grow and change over billions of years!

Tasks: Interns will help filter and organize the spectroscopic and photometric data from the TREX survey to create spatially-matched subsamples of M33 stars, ensuring the data is consistent across different age groups and areas of the galaxy. They will analyze the color-magnitude diagram (CMD) to compare the dynamically hot (spheroid) and cold (disk) stellar populations, looking for trends in metallicity by comparing them with model isochrones. They will study how stellar velocity dispersion changes with age and location in the galaxy by calculating and visualizing these trends, which will help improve our understanding of M33’s inner structure.

AST-04: Characterization of the astrophysical processes that originate with Carbon-Nitrogen Stars

Primary Mentor: Steven Ryan Umbarger (he/him), Esther Kim (she/her)

Number of Interns: 3

Project Description: This research focuses on understanding a special type of star called Carbon-Nitrogen (CN) stars, found in galaxies like Andromeda (M31) and Triangulum (M33). These stars are about 40-50 million years old and in a phase called the Helium-Burning stage, classifying them as young giants or supergiants. However, a puzzling pattern in their nitrogen levels has been observed without a clear explanation. To investigate, data analysis using Python will compare CN stars with variable stars (Cepheids), examining their colors and overlapping data. This study aims to uncover the astrophysical processes behind CN stars and how elements like nitrogen evolve in space.

Tasks: The SIP interns will be working on the following tasks:

Utilize python code and Topcat Astronomy software in order to measure the distance between stars in various catalogs.

Compare Cepheid catalogs to the Keck DEIMOS spectroscopic catalogs in M31 and M33 galaxies.

Produce color magnitude diagrams of star matches between M31 and M33 galaxies and analyze the stages of weak CN stars using the diagram.

AST-05: Finding and Characterizing Variable Stars in the Andromeda Galaxy (M31); Difference Image Analysis

Primary Mentor: Jasmine Fortez(she/her)

Number of Interns: 5

Project Description: This project focuses on uncovering the secrets of variable stars—stars that change in brightness over time—within the Andromeda Galaxy (M31), our closest galactic neighbor. Variable stars are key to understanding the internal processes of stars, revealing insights into their structure, evolution, and life cycles. When a star’s brightness changes, it acts like a cosmic heartbeat, providing astronomers with a rare glimpse into what’s happening deep inside. Some of these stars even serve as cosmic distance markers, helping map the scale of the universe.
Andromeda is the perfect place to study these stars. Since we can’t observe our own galaxy from the outside, studying Andromeda gives us an external perspective—like looking at our sibling in a world without mirrors. The Hubble Space Telescope’s largest digital mosaic ever is of M31, and it provides a sharp, high-resolution view across a vast area with stellar brightnesses captured precisely in six filters across the ultraviolet, visible light, and infrared portions of the electromagnetic spectrum. This tiling pattern of the digital mosaic is such that there is significant overlap between adjacent tiles. Difference image analysis in these overlap areas is the basis of this variable star project.

Tasks: This project studies variable stars in the Andromeda Galaxy (M31) using a technique called difference image analysis. By comparing images taken at different times, we can find stars that change in brightness. We then plot these stars on a color-magnitude diagram to understand their properties better. A key element in this analysis is the point spread function (PSF). The PSF describes how a star, which is a point source of light, appears as a spread-out two-dimensional light pattern in an image. This pattern can change over time due to changes in the instrument focus (In general, PSF variations are caused by changes in the instrument and atmosphere. In our case though, we’re working with Hubble Space Telescope images. Since HST orbits the Earth above the atmosphere, the only source of PSF variations in HST images is telescope focus.), and it affects the strength of the residuals of non-variable stars in the difference image.

Interns will be involved in the following tasks:

Labeling Variable Stars:Carefully examine difference images to mark the positions and important details of stars that vary in brightness.
Documenting Brightness Changes:
Record how the brightness of these stars changes over time.
Plotting on Color-Magnitude Diagrams:
Help plot the labeled stars on a color-magnitude diagram, which helps us learn more about their properties.
Understanding the PSF:
Learn about the point spread function and see how its changes can impact the appearance of non-variable stars in the difference image.

URL: https://app.ubinum.com/lab/raja-uco-lick-observatory/research

URL: https://news.ucsc.edu/2025/01/andromeda-galaxy-mosaic.html

AST-06: Resolved Stellar Populations of Local Group Galaxies: RR Lyrae in the Milky Way Halo, Stellar Disk Kinematics of M31 and M33, and Rare Stars in the MW, M31, M33, and the LMC

Primary Mentor: Minjae Kim (he/him)

Number of Interns: 3

Project Description: In this project, we will explore stars in two nearby galaxies, Andromeda (M31) and Triangulum (M33), using advanced astronomical data. The goal is to uncover the hidden properties of stars that were accidentally captured in large telescope surveys, revealing their unique roles in galaxy formation and evolution. By analyzing the light from these stars and comparing it with their spectra, we can distinguish between stars from the galaxy, the Milky Way, and distant quasars. This research will help us understand the structure, motion, and evolution of galaxies beyond our own.

Tasks: As a student intern, you will work closely with a visiting researcher to analyze real data from two major surveys of the Andromeda (M31) and Triangulum (M33) galaxies. You will learn how to use the analyzing tool to match star light with its spectrum, helping us understand which stars belong to these galaxies and which are contaminants from the Milky Way or distant quasars. We will calculate how neighboring stars affect the light we see and learn how to separate different types of stars. Prior experience in programming (such as Python) would be helpful. If you’re new to programming, i recommend gaining some basic familiarity with it before the internship to maximize your experience. Through hands-on experience, you will develop skills in data analysis, astronomy tools, and gain insights into how scientific research is conducted.

URL: https://campusdirectory.ucsc.edu/cd_detail?uid=pguhatha

AST-07: Spectral Classification of High Mass X-ray Binaries *TSIP

Primary Mentor: Ernesto Ramirez Jr (he/him)

Number of Interns: 4

Project Description: High mass X-ray binaries (HMXBs) are a star system consisting of a very large star and compact object (black hole or neutron star), we observe these binaries with ground and space telescopes. We get information about the star is in the binary by looking at the light. From the star light we can determine what elements make it up and how fast it’s moving. With these observation we can get a better understanding of HMXBs which we think could be sources of gravitational waves and their role in star/galaxy formation.

Tasks: Our work will consist of reading papers/articles, python coding, plotting data, and reading the spectra of stars. Time will be allocated for learning about high mass X-ray binaries (HMXBs), spectra, software we’ll be using, and any other information/techniques relevant to our research. Most of our time will be spent coding in python to go through data and plot our spectra. We’ll be taking notes about our candidate stars from (HMXBs) and classifying them based on their spectra and potentially their radial velocities.

AST-08: Viewing Images and Spectra of Triangulum and Andromeda (VISTA) *TSIP

Primary Mentor: Max Kogan (he/they)

Number of Interns: 4

Project Description: The goal of this project is to study the resolved stellar populations of two of our nearest galactic neighbors, the Andromeda Galaxy (M31) and the Triangulum Galaxy (M33). This will be accomplished by utilizing the datasets from two instruments, the Hubble Space Telescope and the Deep Imaging Multi-Object Spectrograph. During the summer, we will be using the information from these datasets to investigate the velocity distribution of the stars in these galaxies, and consider methods we can take to refine our measurements to produce a more accurate distribution. This will allow us to better understand the history and evolution of these galaxies and ascertain the existence and effects of merger events in the distant and recent past.

Tasks:

Using Python and Jupyter (among others) to interact and manipulate astronomical data files
Using an understanding of the instruments said data was taken with to better utilize said data
Setting up a web-based browser connected to a remote-storage drive to enable widespread access to the data and accompanying software
Using the data to better understand the extragalactic objects in question (M31 and M33, primarily)

AST-09: Understanding the VHE component of Gamma-ray bursts using VERITAS data

Primary Mentor: Madalyn (Maddie) Johnson (she/her)

Number of Interns: 3

Project Description: Gamma-ray bursts (GRBs) are the most powerful bursts of energy in the universe. Telescopes at all wavelengths have detected these high-energy explosions, but there are still many questions about their environment and what produces these bursts. The Very Energetic Radiation Imaging Telescope Array System is a ground-based telescope in southern Arizona that is sensitive to very high-energy gamma rays. VERITAS has taken data on over 100 GRBs to search for the very high-energy component of these GRBs. This project will involve examining all GRB data taken by VERITAS for bursts with accurate positions in order to better understand the characteristics of these high-energy events. Additionally, it will also be interesting to compare Swift X-Ray Telescope (XRT) to VERITAS to see if there is any correlation between the X-ray and the high energy gamma ray components.

Tasks: In this research project, SIP interns will use VERITAS data to search for the detection of very high-energy gamma rays from gamma-ray bursts (GRB). To search for this detection, Interns will use Terminal to access our local computer cluster at UCSC and will learn to use the VERITAS data-analysis software package needed to analyze these GRBs. This project will work on finishing and double-checking the analysis of 100 GRBs observed with VERITAS (from 2006 to 2022) that a previous student started. Additionally, interns will analyze more recent GRBs that VERITAS has followed up on from 2022 to today. Furthermore, interns will compare this analysis with Swift XRT data that has been taken during the timeframe of the VERITAS data. To make this comparison, Interns will use a Jupyter notebook to plot both data sets and interpret their results.

AST-10: Discovering Stars with Machine Learning

Primary Mentor: Zoe Weber-Porter (she/her)

Number of Interns: 3

Project Description: In this project, students will explore the intersection of astronomy and artificial intelligence by building a machine learning model that maps stars onto the Hertzsprung-Russell (H-R) diagram—a powerful tool astronomers use to study how stars evolve. Using real stellar data from the Sloan Digital Sky Survey, students will learn to process and analyze key star properties like temperature, gravity, and metallicity. They’ll train a neural network to predict a star’s metallicity and use those results to visualize star populations across the galaxy. Along the way, students will gain hands-on experience with Python, data science, and astrophysics concepts, while also learning to think like scientists. This project is ideal for students who are curious about space, enjoy working with data, or want to explore how machine learning is used to make discoveries about our universe.

Tasks: Interns will work with real astronomical data from the Sloan Digital Sky Survey to explore stellar properties. Tasks include filtering and preprocessing FITS-format star catalogs using Python, extracting features like effective temperature, surface gravity, and metallicity. Interns will build and train a machine learning model (using PyTorch) to predict metallicity and evaluate its performance using loss functions and test/train data splits. They will visualize results by generating Hertzsprung-Russell diagrams and comparing predicted vs. actual values. Interns will also document their methodology, interpret their results in an astrophysical context, and present their findings at the end of the program.

URL: https://www.linkedin.com/in/zoeemw/

Biomolecular Engineering (BME)

BME-01: Ancient Centromere Spanning Haplotypes Provide Insight into Human Centromeric Satellite Evolution in Telomere-to-Telomere (T2T) Genomes *TSIP

Primary Mentor: Hailey Loucks (she/her)

Number of Interns: 3

Project Description: This project is a computational biology project analyzing the evolution of centromeric DNA in modern humans. The centromere is an important structural component of the chromosome which is composed of repetitive DNA sequences. Due to the unique properties of the centromere, the sequences of DNA next to the centromere can persist unchanged for many generations, keeping a record of human evolutionary history. By studying the evolution of these sequences we can better understand human evolution and our historical relationships with archaic hominins such as Neanderthals.

Tasks: Project is entirely computational. Students will work on the Unix command line to run bioinformatics software to understand evolutionary relationships between DNA sequences, including sequence alignment, clustering, and annotation. Students will also work in python and/or R languages to run analyses and create visualizations. Mac laptops are preferred but any laptop can work.

URL: https://migalab.com/

BME-02: Gene Annotation with Comparative Annotation Toolkit

Primary Mentor: Prajna Hebbar (she/her)

Number of Interns: 3

Project Description: The human genome refers to all the DNA of the human species. Human DNA consists of 3.3 billion base pairs and is divided into more than 20,000 protein-coding genes onto 23 pairs of chromosomes. The human genome also includes noncoding sequences of DNA. Locating these protein-coding and noncoding genes is done through the process of gene annotation. This process actually provides a meaning to the sequence of a species’ genome assembly. There are many software to annotate genomes of different species to find the locations of various genes on them. The Comparative Annotation Toolkit (CAT) is one of them, which I am working on improving. The project aims to study gene annotations produced by CAT and those produced by other methods and compare their accuracy and performance.

Tasks: The first three weeks will be spent on learning and setting up for the actual research which will be done in the latter half of the project. Understand the basics of genomics- what is a genome, assembly, alignment, annotation, etc. Learn about gene annotation in some more depth. Read about the different tools that they will work with. Install tools and download data. Do any required troubleshooting. Run tools on genomes. Analyze and understand the results. Learn to visualize results on the UCSC Genome Browser Compare results across the different tools. Can work with Mac or Windows.

URL: https://cglgenomics.ucsc.edu/

BME-03: Advancing rare disease diagnosis with long read sequencing and pangenomics *TSIP

Primary Mentor: Konstantinos Kyriakidis (he/him)

Number of Interns: 3

Project Description: Become a genetic detective! Despite sequencing whole genomes, roughly half of rare genetic diseases remain unsolved mysteries. Often, the crucial clues hide in complex, repetitive DNA regions – ‘dark areas’ inaccessible to standard ‘short-read’ sequencing. These regions can harbor not just small typos, but also large DNA rearrangements (‘structural variants’ or SVs) that are particularly hard to spot with old methods. In this project we will use powerful long-read sequencing (LRS), which reads much longer DNA pieces, to finally try to illuminate these challenging areas. By exploring real LRS data from these ‘hard’ regions, we will investigate how this technology finds hidden variations (especially SVs) and help us develop more accurate and comprehensive rare disease diagnostics.

Tasks: Learn about genome sequencing and the advantages and disadvantages of each sequencing technology. Understand DNA variations (especially large ‘Structural Variants’ or SVs) and why long-read sequencing (LRS) is essential for exploring complex, repetitive parts of the genome missed by older methods. Learn about genome assemblies and pangenome graphs. Familiarize with bioinformatics tools like genome browsers (e.g., IGV) to visualize real LRS alignments. Analyze LRS data, focusing on specific ‘hard-to-read’ genomic regions implicated in rare diseases and practice identifying SVs and other variations made clearly visible by LRS. Investigate potential gene impacts of discovered variants using online databases. Record your observations and prepare a final presentation of your findings. Mac or Windows laptop will suffice for research.

URL: https://cglgenomics.ucsc.edu/projects/

BME-04: Exploring Genetic Mutations in Neurons: A Cloud-Connected CRISPRi Platform

Primary Mentor: Lucero (Samira) Vera-Choqqueccota (she/her)

Number of Interns: 3

Project Description: This project focuses on developing a cloud-connected platform to study how genetic mutations linked to neurodevelopmental and psychiatric disorders affect neurons. SIP interns will work with CRISPR interference (CRISPRi), a method that allows researchers to turn off specific genes in neurons differentiated from embryonic stem cells. Interns will design guide RNAs (gRNAs) for selected genes, such as SCN2A, which is associated with epilepsy and autism, and help build a user-friendly pipeline to identify top candidates. The project also involves validating the effectiveness of CRISPRi by comparing it to gene knockout models. Ultimately, this platform will enable students worldwide to analyze the activity of neurons with targeted gene downregulation using cloud-connected microscopes

Tasks: Interns will assist in developing a cloud-connected platform to analyze the activity and morphology of neurons differentiated from embryonic stem cells. They will design guide RNAs (gRNAs) for genes linked to neurodevelopmental and psychiatric disorders and help build a user-friendly pipeline for identifying potential gRNA candidates. Interns will help validate the CRISPR interference (CRISPRi) system, focusing on gene regulation, by analyzing data when compared to gene knockout models.

URL: https://mostajo-radji.com

Chemistry and Biochemistry (CHE)

CHE-01: 3D Printing of Novel Ink Formulation for Energy Storage Applications

Primary Mentor: Ella Davidi (she/her)

Number of Interns: 3

Project Description: 3D printing of advanced energy storage devices utilizing carbon and oxide materials for developing new supercapacitors. By leveraging the conductivity and surface area of carbon alongside the pseudocapacitive properties of oxide materials, we can maximize energy storage capacity. In this research project, the SIP mentor and interns will use 3D printing techniques to print carbon and oxide materials for energy storage applications.

Tasks: Interns will be engaged in the following tasks:

3D printing of composite electrodes.
Making electrolyte solutions.
Setting up electrochemical cells.
Performing electrochemical measurements.
Analyzing results of experiments.

CHE-02: Ultrafast synthesis of catalysts for water splitting reaction

Primary Mentor: Tianchen Cui (he/him)

Number of Interns: 3

Project Description: Magnetic Induction Heating (MIH) has emerged as a powerful strategy for synthesizing advanced electrocatalysts specifically for water electrolysis. By enabling rapid and localized heating, MIH allows precise control over catalyst composition, phase structure, and defect engineering—key factors for enhancing both the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). Catalysts synthesized via MIH often exhibit superior catalytic activity, stability, and energy efficiency compared to those prepared by conventional methods. With its scalability and controllability, MIH offers a promising pathway for the development of high-performance water-splitting systems, contributing to efficient and sustainable hydrogen production.

Tasks: Synthesis of catalysts, Eletrochemistry performance test, and Data and characterization analysis

URL: https://chen.chemistry.ucsc.edu/

CHE-03: Urea Oxidation for Wastewater treatment and Green Hydrogen Production

Primary Mentor: Qiu Ren (he/him)

Number of Interns: 3

Project Description: Our project focuses on turning wastewater into clean energy. Many water sources are polluted with urea, a common nitrogen compound that harms ecosystems by causing toxic algal blooms. Instead of letting this pollution go to waste, we use a special reaction called urea oxidation to clean the water while producing green hydrogen, a powerful and sustainable fuel. To make this process more efficient, we are developing low-cost electrodes with advanced materials. This research helps protect the environment and supports the transition to clean energy. Through this project, we will explore chemistry, sustainability, and the exciting potential of renewable technologies.

Tasks: Conduct literature reviews to understand the challenges and opportunities of urea oxidation reaction (UOR) in wastewater treatment and hydrogen production. This includes studying nitrogen pollution, electrocatalysis, and the role of advanced electrodes in enhancing reaction efficiency.

Perform structural characterization and analyze electrochemical data to assess catalyst stability, efficiency, and scalability for real-world applications.”

Design and synthesize catalytic electrodes optimized for UOR, focusing on improving urea oxidation efficiency, ion transport, and gas bubble management to enhance hydrogen production.

Fabricate and evaluate the designed electrodes, using electrochemical techniques to test their performance in wastewater conditions.

URL: https://www.kateringland.com/about/#/hcistudentreadinglist

CHE-04: Nanocatalysts for Electrochemistry

Primary Mentor: Dingjie Pan (he/him)

Number of Interns: 3

Project Description: The recent hydrogen production in industry still depends on natural gas. Water constitutes 71 percent of the earth but the high energy barrier for water splitting has limited the extent of its application. The project aims to develop a cost-effective catalyst for electrochemical hydrogen evolution reaction (HER) by exploring ruthenium/copper alloy nanoparticles. The goal is to overcome the high cost and limited availability of platinum, which is currently the commercial benchmark for this reaction. The SIP interns will spend this summer to learn how to design, synthesize, and analyze new electrocatalysts for water splitting.

Tasks: Conduct Electrochemistry Experiments: Perform electrochemical tests including linear sweep voltammetry (LSV), Tafel plots, stability tests, and electrochemical impedance spectroscopy (EIS).

Prepare Samples for Characterization: Utilize the samples for structural characterization. Prepare the samples according to the requirements of the characterization techniques, such as TEM and XPS.

Plot and Analyze Data: Organize the collected electrochemistry data into graphs and plots. Analyze the data to evaluate the electrocatalytic performance of the ruthenium/copper alloy nanoparticles. Interpret the results in comparison to the benchmarks, such as platinum catalysts. Summarize the findings and draw conclusions based on the analysis.

URL: https://chen.chemistry.ucsc.edu/articles/

CHE-05: Designing High-Energy-Density Rechargeable Zinc Batteries

Primary Mentor: Xinzhe Xue (he/him)

Number of Interns: 3

Project Description: Aqueous zinc batteries (AZBs) are considered to be one of the most attractive candidates for the new generation of energy storage, due to their high capacity and safety. To date, different kinds of cathode materials, electrolytes, and structurally engineered electrodes have been exploited to achieve higher energy density. It is critical to review the state-of-the-art AZB systems, identify the fundamental questions that limit the device’s performance, and design materials to tackle these scientific and technological challenges.

Tasks: Interns will:

Read the scientific literature to review the challenges and opportunities of zinc anode (Zn) in aqueous Zn batteries, and understand the mechanisms and design principles of high energy density AZBs.
Learn to design and prepare electrode materials and electrolytes for AZBs, espeically Zn metal anode.
Learn to design experiments, conduct electrochemical tests and cell assembly.
Learn the data analysis/processing after getting the testing data and data interpretation.

URL: https://li.chemistry.ucsc.edu/

CHE-06: Designing 3D Carbon Materials for Electrochemical Energy Storage

Primary Mentor: Cassidy Christine Tran (she/her)

Number of Interns: 3

Project Description: Developing advanced materials for electrochemical energy storage is critical with the growing demand for sustainable energy. One way of improving electrochemical energy storage devices is through 3D design, which allows us to increase surface area and control the microstructure. In carbon electrodes, one way of creating 3D devices is by 3D printing polymer structures, then carbonizing them at high temperatures in an inert atmosphere. In this project, interns will learn to design, print, and test 3D carbon electrodes.

Tasks: Interns will:

Analyze data collected during electrochemical tests.

Review literature on 3D carbon materials for electrochemical energy storage.

Design and print 3D electrodes (a personal laptop will be useful).

Perform electrochemical tests on 3D electrodes.

URL: https://li.chemistry.ucsc.edu/

Computational Media (CPM)

CPM-01: AI-Mediated Interpersonal Interactions and Self-Formation

Primary Mentor: Eve Wang (she/her)

Number of Interns: 4

Project Description: In this project, you’ll customize an AI mediator to guide conversations with family or friends. By designing how the chatbot thinks and responds in multi-user discussions, you’ll explore how your own thought patterns influence communication.

Tasks: You’ll engage in prompt engineering to design an AI mediator that guides conversations with your family or friends. As you test your AI, you’ll write diary reports reflecting on how your design supported or hindered discussions, what changes you made to improve it, and why. Through this iterative process, you’ll contribute to research on how AI can help teenagers explore self-awareness and navigate their relationships.

URL: https://www.kateringland.com/about/#/hcistudentreadinglist

CPM-02: Exploring Fandom Community Using Social Media and Other Online Platforms to Maintain Friendship, and How LLM Might Play a Role

Primary Mentor: April Zhang (she/her)

Number of Interns: 3

Project Description: I’m seeking to investigate how people in a fandom might build relationship, friendship beyond fan activities. This involves in understand what are the reasons whether fans decide to be friend with each other. Would AI can be a feature to help people to be more close to each other online?

Tasks: Interns might be asked to participant in supporting tasks when we conduct interviews (collecting demographic data of participants, etc), observe, and taking notes, etc. Help with processing qualitative data.

URL: https://www.misfit-lab.com/

CPM-03: An Astro-nomical Study: Documenting PS Trophy Hunting Journeys through Astro Bot

Primary Mentor: Derusha Baskaran (she/her) or (they/them)

Number of Interns: 4

Project Description: For this project, we will document our PlayStation (PS) trophy hunting journeys by attempting to earn the platinum trophy in Astro Bot — 2024’s Game of the Year! Using the user diary method, we will conduct collective autoethnographic research while playing and then analyze our experiences to identify common themes/patterns. This study will contribute to and advance game studies by providing rich insights into player experience types and recommendations for designing reward systems that balance challenge and enjoyment.

Tasks: SIP interns will need the following for their research in this project: – Any computer/laptop or tablet (to document notes & access/upload files) – A PlayStation 5 (PS5) & PS5 DualSense controller – Astro Bot Game (PS5 version) SIP interns will do the following tasks for this project:

Play through the Astro Bot game on a PS5 and try to collect all PS trophies (aka obtain the platinum trophy).
Write detailed notes about your PS trophy hunting experience in a user diary
Discuss and analyze themes from your trophy hunting experience
Create a list of design recommendations for an ideal trophy list 5) Read and synthesize HCI/Games Study literature

URL: https://www.misfit-lab.com/

CPM-04: Situating Non-Human Actors in Nature Based Recreational Apps + Mobile Maps for Accessibility Needs

Primary Mentor: Bhavani (Maya) Seetharaman (She/her)

Number of Interns: 6

Project Description: Many nature based recreations often embrace mobile applications that aid in finding new hiking trails, ideal beaches for surfing, etc. In doing so more individuals are able to access a wider array of natural resources. However, due to this access there are large shifts in the local wildlife behaviors and the biodiversity of the region. Due to which there needs to be another model of design that enables engagement in these spaces without affecting the local wildlife population. The interns will aid the mentor in literature reviews, survey creation, data collection, data analysis, and UI/UX design approaches to build possible prototype solutions for these issues.
Similarly, many mobile map applications today are limited for users with a range of disability needs. Individuals with disabilities often have to struggle against inaccessible routes, infrastructure, and lack of customizable/alternative route formations via mobile map applications. Therefore, we aim to create an alternative map interface that normalizes the experience of individual preferences with regards to their mobility practices by attempting to create more customizable features in mapping tools within UCSC campus. To do this we map the multiple routes within campus through fieldwork, highlight different disability needs that are affected by these routes ranging from unpaved roads to lack of shade that can affect individuals across a spectrum of needs. After conducting these mapping exercises mentees will discuss possible variables and needs to take into account and attempt to create alternative figma prototypes for such mobile applications.

Tasks:

Literature Review
Survey Creation and Dissemination
Qualitative Data Analysis
Fieldwork Mapping
Citizen Science Studies
UI/UX Prototyping in Figma

URL: https://sites.google.com/ucsc.edu/bhavani-seetharaman-cm/home?authuser=0

CPM-05: Food Diaries and Personal Informatics *TSIP

Primary Mentor: Ariel Wang (she/her)

Number of Interns: 4

Project Description: In this work, I will explore how food diaries can be reimagined as personal informatics tools that not only track what people eat, but also invite reflection on emotional, social, and cultural aspects of eating. Moving beyond calorie counting and nutritional metrics, I aim to design food diaries that support meaning-making and identity work, especially among young people navigating their everyday food choices. Through co-creation workshops and speculative design methods, I will investigate how users might integrate interactive features—such as social sharing, mood tagging, or even AI tools—into their food logging practices. This approach seeks to broaden the role of food diaries as tools for self-discovery, mindful eating, and long-term health reflection.

Tasks: Interns will support a research project on food diaries and personal informatics. They will read academic articles and contribute to a literature review on related topics. Interns will help conduct qualitative research, such as diary studies, interviews, and design probes with participants. They will assist with organizing and analyzing qualitative data to uncover patterns and insights. Based on findings, interns will brainstorm and sketch potential design directions that support personal reflection and healthy eating. This is a great opportunity for students interested in human-computer interaction, health technologies, or social media and identity to gain hands-on research and design experience. Mac or Windows laptop is required.

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

CPM-06: Augmented Creativity or Co-Creation: Understanding Human-AI Collaboration in Design Workflows

Primary Mentor: Yuki Yin (she/her)

Number of Interns: 4

Project Description: This project aims to explore how AI-augmented features in modern design tools—such as Figma AI, Miro Assist, and Canva Magic Studio (AI Suite)—are influencing designers’ creative practices. How do designers interact with AI-augmented features in everyday design tools? Are these tools changing how designers think, collaborate, or create? Do they feel like collaborators, productivity boosters, or something else?
By studying how these tools support tasks like wireframing, brainstorming, and Interface design, the project investigates whether users perceive AI tools in their design workflows. We will first conduct tool exploration and then do interviews and observational studies with designers using AI-facilitated design tools. We aim to understand how these technologies shape ideation, visual design, creative control, and inform the design of future AI-augmented tools.

Tasks: Interns will explore how AI features in popular design tools (like Figma AI, Miro AI, and Canva) are used to support creativity and design thinking. They will test out these tools, document their experiences, and help analyze how AI assists in tasks like brainstorming, layout suggestions, and organization. Interns will also need to design and conduct interviews or observational studies with users and contribute to identifying patterns in how people interact with AI in design. Prior experience with visual design, UI/UX, or tools like Figma is preferred. This project is ideal for students interested in design, technology, and human-computer interaction.

URL: https://tech4good.soe.ucsc.edu/

CPM-07: Analyzing Metaphors in Agent-Based Game Design Spaces

Primary Mentor: Kyle Gonzalez (he/him)

Number of Interns: 3

Project Description: Although there are a few concrete examples of AI-based game design, we do not yet have a methodology clearly showing how to do AI-based game design research. In this project we gather data by playing a wide variety of agent-based games (e.g. Cities Skylines 2, Totally Accurate Battle Simulator, Oxygen Not Included, …), and use a grounded theory approach to elicit the underlying metaphors that enable players and designers to make sense of agent dynamics. Taking stock of existing metaphors in agent-based games allows us to clarify novel ones, and understand how metaphors for AI techniques scaffold extensive portions of design space.

Tasks: Reading and discussing background literature on game design, design spaces, and grounded theory. Preparing a presentation on work completed this summer (Interns just need any laptop that allows them to use text-processing, email, Discord, and online group collaboration tools). Practicing research skills including qualitative and interpretive analysis of games and game design. Playing and observing others play video games in a reflective way. Regularly reviewing results as a group and writing short reports

URL: https://eis.ucsc.edu/

CPM-08: Causeway: Evaluating a web platform for scaling experiential learning through micro-roles

Primary Mentor: Pragna Chennuri (she/her)

Number of Interns: 3

Project Description: While educational technologies have scaled content-based learning, they have struggled to scale experiential, project-based learning. Causeway is a web platform that models learning after the workplace, organizing the learning process around small experiential “micro-roles.” These micro-roles are the building blocks for two structures: learning pathways that scaffold skill development, and project hierarchies that break down complex work into manageable steps. This approach helps learners understand how their skills contribute to real-world projects and enables them to start contributing while still learning. Causeway supports both fully online learners and those participating in programs that integrate hands-on, team-based project work. Thus far, we have developed parts of the platform but have not conducted formal studies on the experience of learning on the platform, which we plan to do this summer.

Tasks: Over eight weeks, students will set up their Angular environment, complete onboarding, and attend lab orientations. They’ll explore Causeway, identify usability issues, and document feedback. Weeks 2–5 focus on skill-building and iterative usability testing. Students will also engage in group critiques and submit usability reports on Causeway. In Weeks 6–7, they finish conducting usability studies, and finish all the skill building activities. Students will start preparing SIP presentations with peer feedback. The program concludes in Week 8 with finalized presentations delivered on Presentation Day (August 9, 2025). Throughout, students gain technical skills, practice collaborative critique, and contribute to improving the Causeway platform through user-centered design.

URL: https://tech4good.soe.ucsc.edu

CPM-09: Exploring the use of Generative AI for creating experiential learning content

Primary Mentor: Audrey Ostrom (she/her)

Number of Interns: 3

Project Description: Our team will be exploring how Generative AI can be used to create experiential learning content, specifically in the context of expanding the content on a new learning platform, Causeway, which is designed to provide learners with real-world, hands-on experiences in software development. The platform organizes learning into “micro-roles,” small tasks that break down complex projects into manageable steps, simulating real-world job responsibilities. Students will work on projects like building web applications – gaining valuable skills in coding, problem-solving, and collaboration. By progressing through these micro-roles, learners can develop the expertise needed for future careers, bridging the gap between classroom learning and real-world work. Thus far, all the material has been created manually, but the time-intensive nature of creating this material is a major obstacle in creating these kinds of experiences. We’d like to explore how generative AI might be able to overcome these challenges, and what is needed to do so effectively.

Tasks: Interns will gain hands-on experience with web development using Angular, HTML, CSS, TypeScript, and Firebase. They’ll also explore generative AI tools(e.g. OpenAI APIs, GPT models, prompt engineering, etc.) to create new platform content. Additionally, interns may do some UX research, which involves reviewing prior research, analyzing qualitative and quantitative data, and designing and conducting usability studies of various platforms. No prior experience is needed since all interns will be onboarded by the mentor. Any laptop should be sufficient for the work planned this summer.

URL: https://tech4good.soe.ucsc.edu/

CPM-10: Scaffolding Research Paper Reading with AI

Primary Mentor: David Torres-Mendoza (he/him)

Number of Interns: 3

Project Description: How can we make it easier (and more interesting) for students to read and talk about research papers? In this project, we’ll explore how tools like NotebookLM (a Google AI product) can support students in reading research papers more confidently and collaboratively. Interns will test AI-assisted reading workflows, identify where the technology helps or falls short, and design a repeatable process that other students could use. Along the way, we’ll explore big ideas about motivation, learning, and peer discussion — and we’ll think critically about how AI might support or transform the way students read and talk about complex ideas together.

Tasks: How can we make it easier (and more interesting) for students to read and talk about research papers? In this project, we’ll explore how tools like NotebookLM (a Google AI product) can support students in reading research papers more confidently and collaboratively. Interns will test AI-assisted reading workflows, identify where the technology helps or falls short, and design a repeatable process that other students could use. Along the way, we’ll explore big ideas about motivation, learning, and peer discussion — and we’ll think critically about how AI might support or transform the way students read and talk about complex ideas together.

URL: https://tech4good.soe.ucsc.edu/

CPM-11: Making for Tangible and Pleasing Multimodal Interactions

Primary Mentor: Sol Choi (she/her)

Number of Interns: 4

Project Description: This project aims to look for interns who will explore and design tangible tools for understanding meaningful moments of food practices. It will explore how teens reflect on meaningful and meaningless interactions on social media, and how they might envision new tools—such as a personalized food diary—to support their digital and everyday well-being. The final outcome of the session will be creating and prototyping tangible food diaries, that will explore ways to account for different sensory information other than visual, and capturing the moments of food practices; example outputs include scented maps and snackable mood cards. It will use low-fi prototyping tools to enable the meaningful making of the conversations that will spawn through talking about food on social media!ut how AI might support or transform the way students read and talk about complex ideas together.

Tasks: SIP Interns will design a small, interactive experience (physical, digital, or hybrid) that evokes a positive emotional response — such as joy, calm, curiosity, or nostalgia — while acquiring small scale of prototyping skills and apply design thinking into the design. Interns will learn to design interactions that feel good, not just work well — a skill that companies increasingly value as AI becomes more integrated into everyday life. The laptops will have Arduino installed and are capable of installing softwares.

URL: http://www.dontwantnotrouble.com/multi

CPM-12: Game Design Tool Design

Primary Mentor: Jared Pettitt (he/him)

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 the goal of this research project is to design and develop a prototype interface for a game creation tool, using JavaScript. If the SIP interns are interested in making games, in software engineering, or in interface design, this will be an interesting project to work on.

Tasks: Interns will be using javascript, typescript and modern web app libraries to compose and design a game design tool around a javascript library called crisp-game-lib.

Computer Science/Computer Engineering (CSE)

CSE-01: Neural Network Implementation and Deployment: From Scratch to Advanced Libraries

Primary Mentor: Pooneh Safayenikoo (she/her)

Number of Interns: 3

Project Description: Deep learning drives transformative innovations in artificial intelligence. This project empowers SIP interns to explore neural network fundamentals by implementing a simple model from scratch using Python. Interns then transition to advanced deep learning techniques with powerful libraries such as PyTorch, designing and deploying practical applications including cutting-edge large language models (LLMs). They will gain experience building deep neural networks featuring convolutional and fully connected layers and learn modern best practices in model development and deployment. Throughout the project, interns will engage with technical literature and enhance their coding proficiency.

Tasks: Explore Fundamentals:

Study neural network and large language model architectures and theories.

Implement Basics: Code a simple neural network from scratch in Python.

Embrace Deep Learning Libraries: Build advanced models using PyTorch.

Design and Deploy: Create applications to deploy neural networks and language models for real user requests.

Evaluate and Document: Assess model performance and document findings with insights from current technical literature.

CSE-02: Instructed Chain-of-Thought reasoning for information verification and interpretability

Primary Mentor: Peiyu(Olivia) Wang (she/her)

Number of Interns: 3

Project Description: The LLM chain-of-thought (COT) reasoning capability has gained a lot of attention recently; however, it is not without limitations. Currently, COT is unstructured, meaning the result can come in different shapes. making it hard to verify information. Moreover, if important information is missing from the COT reasoning, it will make it hard, if not impossible, to understand the reasoning. I am proposing a project of applying a neuro-symbolic approach to COT reasoning by designing the structure of the “chain”, and instructing LLM to follow this structure to generate reasoning. This approach will standardize and streamline the process, making it possible to verify information and help users understand the reasoning behind the decisions.

Tasks:

Interns should conduct literature reviews on recent COT and neuro-symbolic research, and summarize the advancement and limitations
Interns should design the process of the “”instruction”” for COT
Interns should design the verification techniques (either automatic or manual) for COT
Interns should design tests to check user’s understanding after reading the COT understanding”

CSE-03: Deep Learning Models for Data-driven Lagrangian Data Assimilation in Ocean Dynamics

Primary Mentor: Niloofar Asefi (she/her)

Number of Interns: 3

Project Description: My project is about artificial Intelligence and advanced deep learning models in climate data including ocean science. The lack of sufficient data is a major problem in ocean science. Because it is difficult to monitor the deep ocean everywhere, at all times, there aren’t many observations. To fill in the gaps, my project makes advantage of deep learning, an effective type of artificial intelligence. Deep learning learns directly from real ocean data and can replicate entire ocean patterns, even with very limited input data, in contrast to standard methods that rely on complicated physics and assumptions. By using less data and producing more precise and realistic results, this aids in our understanding of ocean currents and climate systems.us systems that can operate in diverse environments, from search-and-rescue to industrial automation.

Tasks: The SIP interns will:

Learn how various deep learning models are applied to climate and ocean domains;

Gain foundational knowledge in machine learning and deep learning;

Understand key challenges in oceanography and learn how to process data for use in ML models;

Complete assigned coding challenges in Python and present their solutions;

Explore different evaluation metrics to assess model performance;

Learn how to conduct and present novel research in applied machine learning for climate data and forecasting;

Present their findings to the class while improving their presentation and communication skills.

The interns will need access to a laptop for this research project. Higher resource configuration helps faster AI training, but it’s not required.

URL: https://sites.google.com/view/ashesh6810/people?authuser=0

CSE-04: Graph-Based SLAM Simulation in Python for Differential Drive Robots *TSIP

Primary Mentor: Carlos Isaac Espinosa Ramirez (he/him)

Number of Interns: 3

Project Description: This project introduces students to Simultaneous Localization and Mapping (SLAM) using a graph-based approach. We will simulate a differential drive robot in Python, focusing on how it collects sensor data and constructs a map while estimating its own position. By examining key algorithms and coding techniques, participants gain hands-on experience bridging theory and practice in robotic navigation. This work supports broader research on robust, autonomous systems that can operate in diverse environments, from search-and-rescue to industrial automation.

Tasks: Interns will work with a Python-based simulator to explore Graph-Based SLAM using a differential drive robot model. Tasks include setting up and modifying the simulator, generating synthetic sensor data, and writing code to build and optimize a pose graph. Interns will study how robots localize themselves and map unknown environments. They will also visualize results and document their findings. Each intern will need a laptop (Windows, macOS, or Linux) capable of running Python 3 with PyQt5 and pyqtgraph installed. By the end of the program, interns will gain hands-on experience with core robotics and autonomous navigation concepts.

URL: https://asl.soe.ucsc.edu/home

CSE-05: Enhancing Academic Integrity Systems: Developing Advanced MOSS Tools for Automated Plagiarism Detection

Primary Mentor: Suryakiran Valavala (he/him)

Number of Interns: 3

Project Description: This project builds on my work developing innovative tools to enhance the MOSS (Measure of Software Similarity) system used for detecting code plagiarism in academic settings. Interns will contribute to designing a web-based platform that improves how instructors review and manage academic integrity in programming courses. You’ll gain hands-on experience with real-world software development, learning web technologies, database design, and algorithm optimization. This research directly addresses the growing challenges of maintaining academic integrity in computer science education while providing you with valuable skills in full-stack development, data analysis, and ethical computing.l automation.

Tasks: Interns will develop and enhance tools for the MOSS (Measure of Software Similarity) plagiarism detection system. Tasks include: (1) Analyzing existing MOSS outputs and identifying patterns in code similarity reports; (2) Developing a web-based dashboard for visualizing plagiarism detection results; (3) Creating automated tools to process historical submission data efficiently; (4) Optimizing algorithms to improve detection accuracy; and (5) Implementing user-friendly interfaces for instructors to review potential cases. Interns will gain hands-on experience with full-stack development, data visualization, and algorithm implementation while contributing to academic integrity systems.

URL: https://github.com/suryaCS719

CSE-06: Targeted Training and Sampling Techniques for Promoting Robustness of Autonomous Agents

Primary Mentor: Kay Vargas (he/him)

Number of Interns: 3

Project Description: Many autonomous systems such as self-driving cars, drones, or robots rely on a form of machine learning known as reinforcement learning (RL) in order to ‘learn’ how to perform complex tasks. When these systems are deployed in the real world it is critical to ensure their safety; however, this is fundamentally challenging due to the complexity of the environments in which they operate. This project seeks to explore how the use of the Scenic probabilistic programming language and targeted sampling can supplement traditional approaches to training RL agents to enhance their safety and robustness. In this project students will have the opportunity to train, develop, and test RL agents and work towards improving these models through targeted simulation and testing.

Tasks:

Learn how to generate simulations using Scenic and VerifAI

Students will need access to a computer (Any laptop)”

Develop understanding and familarity wtih reinforcment learning principles

Modify the provided trainign pipeline with their own experiments or design new scenarios where they can implement their own agent

Conduct data analysis to explore the benfits or drawbacks of different sampling approaches

URL: https://scenic-lang.org/

CSE-07: Enhancing Indoor Localization Using Machine Learning Models with the 802.11

Primary Mentor: Nayan Bhatia (he/him)

Number of Interns: 4

Project Description: This project explores how everyday WiFi signals, normally used for the internet to aid in tasks like indoor navigation, fall detection, and more. As WiFi waves bounce off walls, furniture, and people, they slightly change. We use those changes to “sense” what’s happening in a room without needing cameras or wearables. With tools like Channel State Information (CSI) and machine learning, we can detect movement, count people, or even monitor heart rate. It’s private, low-cost, and works with existing WiFi. Our goal is to show how useful and powerful WiFi can be beyond just getting you online.

URL: https://inrg.engineering.ucsc.edu/people/nayan-bhatia/

CSE-08: Exploring Neural Architectures

Primary Mentor: Brian Mak (he/him)

Number of Interns: 3

Project Description: In this project, interns will explore the mathematical and programming foundations of neural networks, gaining proficiency in essential concepts and Python libraries for deep learning. Students will learn how neural networks process data through hands-on exercises applying linear algebra, calculus, and probability theory. The project culminates in creating and training a custom language model based on the transformer architecture, with opportunities to experiment with novel modifications to attention mechanisms or architectural components. Interns will present their findings, analyzing how their innovations affect model performance and discussing implications for the field of natural language processing.

Tasks: For the first half of the program interns will be asked to study the basics of neural networks and familiarize themselves with the python libraries needed to implement them. The interns will then be asked to implement and train a baseline transformer language model. Once this has been completed, several experiments will be carried out to determine the effectiveness of various novel modifications to the transformer architecture. Interns will require a laptop of any kind for participation in this project. A laptop (of any kind) will be necessary for this project.

URL: https://jflanigan.github.io/

CSE-09: Instrumenting & Testing a Game Boy Emulator *TSIP

Primary Mentor: Jayaraj Jayakumar (he/him)

Number of Interns: 3

Project Description: Are you curious about how retro gaming systems are brought to life in software? In this project, you’ll help enhance a Game Boy emulator by adding new logging and diagnostic features that track CPU instructions, memory reads/writes, and other hardware events in real time. By systematically testing these logs with known game ROMs, we’ll reveal how an emulator reproduces the Game Boy’s hardware behavior—paving the way for more advanced hardware verification techniques. This work directly supports our broader research on bridging the gap between software-level emulation and hardware-level design verification, ultimately leading to more reliable and efficient hardware.

Tasks: During this internship, you will dive into the inner workings of a Game Boy emulator, focusing on event tracking and software testing. Your primary tasks will include identifying key places within the emulator code where CPU instructions, memory operations, and interrupts occur, then implementing logging features for these events. You’ll learn to compile and run test ROMs, collect and analyze logs, and compare execution paths for different games. Finally, you’ll work on refining and presenting your findings with clear documentation and basic coverage metrics. Through this, you’ll gain firsthand experience in code instrumentation, debugging, and software-based hardware verification concepts. (Interns simply need a personal laptop—Windows or Mac—that can install a standard C++ development environment and run an emulator. Basic specs: modern processor, at least 8 GB RAM, and capability to compile C/C++ code.)

URL: https://masc.soe.ucsc.edu/index.html

CSE-10: Detecting Faulty Drone Behaviors with Large Language Models

Primary Mentor: Diego Esteban Ortiz Barbosa (he/him)

Number of Interns: 3

Project Description: Large Language Models (LLMs) and Multi-Modal Large Language Models (MLLMs) have taken the world by storm and have shown their potential in a wide array of different contexts. Their capabilities have been used to help in real-life decision processes and make data more accessible to understand and process. More recently, MLLMs have started to play a significant role in the robotic field, with several projects already testing their applicability in tasks such as planning or navigation. The mentor’s research group aims to further explore MLLM capabilities in the cybersecurity context by testing its abilities to identify dangerous or strange situations that may present dangers to a system. In this research project, the mentor aims to use MLLMs to detect anomalies inside a cyber-physical system, such as drones. In this research, the SIP interns and mentor will test how MLLMs can identify anomalies regarding a specific sensor by interpreting its image feed and other sensor behaviors that may indicate it is under attack or has been compromised in another way.

Tasks: The SIP interns on this research project will: (1) become familiar with the Drone simulation system Gazebo; (2) familiarize themselves with LLMs and build a basic model; (3) help interface their LLM with Gazebo; and (4) test the ability of the MLLM to detect faults sent from a simulated sensor. Laptop with virtualization capabilities and an independent GPU.

CSE-11: Discovering New Applications and Topologies for Lightweight Decentralized Deep Learninguage Models

Primary Mentor: Harikrishna (Hari) Kuttivelil (he/him)

Number of Interns: 3

Project Description: In recent years, there’s been a lot of focus on big, large-scale AI and machine learning, from the successes and challenges of large language models that power tools like ChatGPT to the building of powerful but resource-hungry data centers to power the increasing number of AI-powered applications and services. However, many of the most useful or necessary applications of AI – including recommendation systems, remote environmental monitoring systems, and image recognition – can be handled between the devices we already have with us, like phones and Raspberry Pis. In this project, we explore the growing field of decentralized edge intelligence – small-scale and lightweight AI enabled by collaboration between devices. We’ll hypothesize and consider potential applications of this new paradigm of AI and observe the effects of different real-world network topologies on decentralized edge intelligence systems.

Tasks: Interns will have the opportunities to: (1) read existing works in edge intelligence and come up with potential application scenarios; (2) find datasets relevant to proposed application scenarios and develop learning models and network configurations; (3) observe the performance of proposed applications using a decentralized deep learning simulator; and (4) create easily understandable data visualizations to effectively present observations of the proposed applications. Interns will learn how to read and contribute to academic literature. For building our systems, we’ll be using Python 3 to program and PyTorch as our main deep learning framework. Students should have access to a Mac, Windows, or Linux computer.

URL: https://inrg.engineering.ucsc.edu/project/del/

CSE-12: Synchronization Methods for Applications in Far Memory Systems *TSIP

Primary Mentor: Esteban Ramos (he/him)

Number of Interns: 3

Project Description: To make applications run fast they need to be able to do work in parallel. This requires applications to be carefully designed to be able to share data while preventing any failures from occurring. Key to doing this is the mutex, a low level data structure that permits independent processors to access the same data without getting in each other’s way.

This project seeks to be a concrete introduction to multiprocessor programming. Students will receive a primer in the basics of systems programming, parallel applications, and on how to make fast software. This should equip them with all the skills necessary to implement the fundamental building block of parallel applications, the mutex.

The mutexes written will then be used to study novel interconnects that enable applications to use far memory. Far memory allows applications to work with data that exists on a different machine as if it was nearby. This is of special interest for large scale distributed applications in which the cost of parallelization is significant, as it requires data to be sent over the network. Yet, as these interconnects are so new their performance characteristics are poorly understood. The research impact of this project is to study these novel interconnect technologies by using the mutexes implemented by the students.

Tasks:

Learn how to program systems software in C

Learn how to write fast parallel applications

Implement a mutex by the end of the program that will run on research hardware

Measure and graph the performance of software

Read foundational computer science papers and discuss them

Either Mac or Windows laptop is okay

Earth and Planetary Sciences (EPS)

EPS-01: Exploring Evolutionary Change in Response to Climate Change 51 MYA

Primary Mentor: Jay Fearon (they/them)

Number of Interns: 5

Project Description: It is accepted as scientific consensus that sudden changes in earth’s climate can and have caused mass extinctions and rapid ecological changes. In recent years, our estimations of past climate change have become more accurate and precise. This project bridges paleoclimate and paleoecology by studying ostracod evolution before, during, and after the Paleocene-Eocene Thermal Maximum (PETM), an abrupt early Cenozoic warming event 51 million years ago. Ostracods are tiny crustaceans about the size of a grain of sand. Our goal is to see what evolutionary trade-offs ostracods made to survive high water temperatures and ocean acidification in their rapidly changing world.

Tasks: Interns will extract ostracod fossils from sediment samples using a light microscope, and measure them for length, width and weight. These metrics will provide a case study of how ecological populations react to climate change, as well as how ostracod body shape evolved over the short term to deal with stressful conditions. Interns will learn how to read a scientific paper and gain skills in data manipulation, data wrangling, statistics, and commonly used methods in invertebrate paleontology. Previous experience with light microscopes is preferred but not required.

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

EPS-02: Reconstructing 50 million years of Marine Mammal Behavior with Trace Metal Stable Isotopes *TSIP

Primary Mentor: Tessa Holzmann (she/her)

Number of Interns: 3

Project Description: My project explores how seals and whales survived in changing oceans 50 million years ago to today by studying the isotope chemistry of their teeth and bones. Every animal’s behavior leaves chemical “fingerprints” in their skeletons, and I use these isotopic fingerprints to investigate what ancient and modern animals ate and where they lived. I necropsy and collect modern marine mammal skeletons from local strandings to see marine mammals adapted to changes in their environment over time. This helps us understand how they might respond to challenges today, like climate change and habitat loss.

Tasks: Basic chemical laboratory work: pipetting, mixing chemicals, working in the fume hood, weighing Paleontological sampling: drilling teeth/bones, pretreating fossil material for isotope analysis Mass spectrometer data collection & analysis Statistical Analysis Necropsy/Autopsy of local stranded whales and seals to collect bones and teeth (optional but fun) Collection of fossils and rocks from field areas in Northern California.

URL: https://sites.google.com/view/tessaholzmann/bio?authuser=0

Ecology and Evolutionary Biology (EEB)

EEB-01: Decoding Hibernation: Gene expression Changes in Grizzly Bear Blood *TSIP

Primary Mentor: Alexis Enstrom (she/her)

Number of Interns: 3

Project Description: Hibernation in brown bears (Ursus arctos) includes major physiological changes, enabling them to endure prolonged periods of fasting and immobility. During hibernation, the bears undergo changes such as reductions in body temperature, metabolic suppression, and temporary insulin resistance. Yet, bears remarkably evade the detrimental health effects associated with prolonged inactivity in humans. My project compares blood samples from brown bears at different time points to investigate gene expression changes associated with hibernation using RNA-sequencing (RNAseq). Identifying genes with significant changes across seasons offers a unique perspective on systemic adaptations, including changes in the immune system and metabolic regulation. The findings from this project have implications for human medicine, including advancements in treating metabolic disorders, identifying mediators of metabolic homeostasis, and potential therapeutic approaches for muscle-wasting diseases.

Tasks: Interns will gain hands-on experience in both wet lab and computational biology. They’ll learn essential molecular techniques such as pipetting, RNA extraction (from brown bear blood!!), PCR/qPCR, and RNA quality assessment on a bioanalyzer. In the dry lab, they’ll practice Bash scripting (Mac is preferred but not required) on a high-performance computing cluster, run RNA-seq analysis pipelines, and use R (will need to download RStudio) and Python for data visualization. Interns will also engage in literature review, protocol writing, and scientific communication. This program will introduce real-world genomics research while building foundational lab and coding skills. This work is for students interested in molecular biology, bioinformatics, and/or wildlife conservation!

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

Economics (ECO)

ECO-01: The Impact of the Ban on Willful Defiance Suspension on Teacher’s Transfer

Primary Mentor: Seono Yun (he/him)

Number of Interns: 4

Project Description: In 2024, California Governor Gavin Newsom signed a bill banning “willful defiance” suspensions (WDS) in all K-12 public schools. Using datasets from the California Department of Education (CDE), I am analyzing the impact of this policy on student and teacher behavior. Preliminary findings suggest that students are staying longer at school and showing increased willingness to study. However, teachers report losing control of their classrooms and experiencing higher levels of stress. I plan to support these hypotheses with data analysis.

Tasks: Connecting Social Events to Analysis Learning Basic Statistics Managing Datasets Computer Programming (Excel & Python)

URL: https://economics.ucsc.edu/

ECO-02: The Impact of Neighborhood Crime on Educational Outcomes: Evidence from U.S. Metropolitan Areas

Primary Mentor: Sajad Tahavori (he/him)

Number of Interns: 4

Project Description: What if big crime data could help us understand where students go to school‚Äîand why? This project dives into millions of real crime records from cities like Los Angeles, Chicago, and New York to explore how neighborhood safety shapes school enrollment. We clean and organize massive datasets, map crime near schools, and uncover patterns in how families respond. Do they transfer schools? Avoid certain areas? Move altogether? By turning raw data into real insights, this research shows how big data and smart analysis can help make schools safer, more equitable, and more accessible‚Äîespecially for students living in high-crime neighborhoods.

Tasks: Interns will help explore how neighborhood crime impacts school outcomes in major U.S. cities. Tasks include reviewing research articles, cleaning and organizing large datasets, and working with school and crime data from multiple sources. Interns will assist in finding patterns, summarizing key statistics, and highlighting interesting facts. This project offers hands-on experience with data analysis, mapping, and research writing‚Äîperfect for students interested in education, cities, data science, or social equity.

ECO-03: Decoding the Mispricing Factor Zoo: Insights from Arbitrage Trading

Primary Mentor: Yuchao Li (he/him)

Number of Interns: 3

Project Description: Have you ever wondered why some stocks seem mispriced? Our project, “Decoding the Mispricing Factor Zoo: Insights from Arbitrage Trading,” is like a detective story in finance. We search for hidden signals—called factors—that reveal when stocks are priced too high or too low. Using real trading data, we determine which signals indicate true market risk and which are simply mistakes. This research not only helps investors make smarter choices but also advances our goal of understanding complex financial systems. Join us on this exciting journey into the stock market’s secrets!

Tasks: Imagine being a detective in the world of finance! As an SIP Intern on our team, you’ll embark on a research adventure to uncover the secrets behind mispricing factors. Your mission is to dive into academic papers, track down the original author’s claims about these mysterious signals, and document what they mean. Using cool data analysis tools, you’ll summarize, compare, and report your findings. This hands-on project not only sharpens your research skills but also fuels our groundbreaking work on “Decoding the Mispricing Factor Zoo.” Join us this summer and become a financial detective on a thrilling quest to crack market mysteries!

URL: https://economics.ucsc.edu/index.html

Education (EDU)

EDU-01: Project Leverage

Primary Mentor: Carla Suarez Soto (she/her)

Number of Interns: 3

Project Description: Project leverage aims to support students in mastering STEM concepts while also developing their language skills by training bilingual STEM teachers. Project Leverage is a partnership between several universities to support middle and high school STEM teachers who work with bilingual students. The program helps teachers learn new teaching methods and complete the requirements for a bilingual teaching credential. We focus on professional development that builds on students’ strengths and improves their learning opportunities by connecting STEM subjects with literacy. Teachers take courses on bilingual education and content literacy, along with receiving hands-on coaching, to help them use effective teaching strategies.

Tasks: SIP interns will play a key role in Project Leverage by transcribing and analyzing interviews with bilingual teachers who participated in the program. They will develop qualitative research skills by identifying themes in teacher experiences and will also look through teacher surveys. Interns will also gain experience finding credible research articles, reading academic papers, summarizing key ideas, and writing literature reviews. Additionally, interns will be introduced to quantitative analysis while assisting in program evaluation. They will have opportunities to join research meetings, observe other projects with Dr. Mosqueda’s team, and practice presenting research findings, which will help them grow as emerging researchers and critical thinkers.

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

Electrical Engineering (ELE)

ELE-01: Electrical and Computer Engineering

Primary Mentor: Kimia Gholami (she/her)

Number of Interns: 3

Project Description: Image segmentation is a fundamental part of computer vision that allows computers to identify and differentiate parts of an image, making sense of complex visual data. In this project, we explore various Artificial Intelligence (AI) models to understand how effectively they can segment images and distinguish pixels related to an object from the background. By comparing different models and analyzing their performance, we uncover ways to improve the accuracy of various models. The goal of this work is to deeply understand current models of AI in visual processing and contribute to advancements in this field.

Tasks: Gain hands-on experience with artificial intelligence (AI) models by working on various image segmentation tasks in medical imaging, robotics, and autonomous driving. Interns will preprocess image data, train AI models, and evaluate their performance using accuracy metrics. By experimenting with different segmentation techniques, they will gain insights into how AI interprets visual information. They will also visualize and analyze results to identify areas for improvement. This project provides an exciting opportunity to explore the current AI models in image segmentation tasks while contributing to advancements. No prior experience is required—just curiosity and enthusiasm for technology and problem-solving!

ELE-02: Recovery of composite refractive index of environmentally aged pure ozone AlOx protective coatings on silver mirrors from reflectance spectra using dispersion relation modeling

Primary Mentor: Soren Tornoe

Number of Interns: 3

Project Description: Silver (Ag) excels as a metal-base for astronomical mirrors for its high reflectivity across the visible to infrared spectral range. However, Ag degrades quickly in an observatory environment, necessitating a protective coating like aluminum oxide (AlOx). High-purity ozone (PO) as an atomic layer deposition (ALD) oxygen precursor has shown potential as a better precursor over the more conventionally used H2O, with improved film quality and reduced deposition times. After enduring high humidity high temperature (HTHH) testing PO boasted a minimal reflectance reduction (~12%) over H2O (~30%). The goal of this project is to elucidate the composite material properties unique to each of the HTHH tested PO samples. This will be done by performing dispersion relation modeling on collected reflectance data to recover the refractive index spectra for each PO sample.

Tasks: Interns will model and optimize the material properties of AlOx coated Ag mirrors by writing code using a programming language like MATLAB/GNU Octave and developing dispersion relation models to calculate the refractive indecies of the coated mirror samples. The mentor will teach a basic understanding of atomic layer deposition, light interactions on multilayered thin film structures, complex refractive index and holomorphicity, as well as go over the principles behind dispersion relation modeling; it’s uses and its shortcomings. Programming experience is strongly recommended but not required. A computer capable of running MATLAB/GNU Octave or other similar complex mathematics software is required.

ELE-03: Autoencoders In Wiretap Channels *TSIP

Primary Mentor: Adam Rammaha (he/him)

Number of Interns: 3

Project Description: This project explores the use of deep learning-based autoencoders for secure communication over wiretap channels. Specifically, we design and train neural network models that encode messages in a way that allows the legitimate receiver (Bob) to decode them reliably, while minimizing information leakage to an eavesdropper (Eve). Our system operates in the presence of Gaussian noise and simulates varying levels of signal-to-noise ratio (SNR) for both Bob and Eve. We analyze system performance through metrics such as Bit Error Rate (BER), Block Error Rate (BLER), and information leakage upper bounds. The architecture is flexible and enables experimentation with different loss weighting strategies to control trade-offs between reliability and secrecy. This work aims to improve upon existing models and lays the foundation in the area of physical-layer security using deep learning.

Tasks: Interns will work on developing and improving deep learning-based communication systems over wiretap channels. Tasks include implementing and training autoencoder models, evaluating performance through BER, BLER, and leakage metrics, and experimenting with different network architectures and training strategies. Interns will gain hands-on experience with Python, TensorFlow, and secure communication concepts, while also contributing to research-level code.

ELE-04: Exploring the Technology Behind (NFC) Systems and Their Influence on Biosensing Applications

Primary Mentor: Gamze Onuker (she/her)

Number of Interns: 3

Project Description: Near Field Communication (NFC) technology is constantly in our everyday routines, facilitating quick transactions with credit cards, personal verification, and commercial ease. However, do we grasp the effectiveness of this wireless sensor network in connecting biosensors with caregivers? Recently, an increasing number of wireless sensors have been utilized for medical applications. This trend is driven by their advantages, such as significant reductions in device weight, volume, and thickness, attributed to the benefits of a battery-free power supply method. The goal of this summer internship is to provide an overview on NFC technology, covering the electronic design, computational processes, and existing research on systems that integrate NFC with biosensors for biomedical applications. Interns will begin by mastering the skill of effectively reading and understanding academic papers related to the field. The mentor will oversee their progress through the stages of literature review, followed by the development of a very basic simulation system that models the communication between two Near Field Communication (NFC) devices.

Tasks: The interns will:

Do a literature review on biosensors and their applications that utilize NFC
Investigate the basic circuit designs for this wireless communication technology
Be introduced to a programming platform called MATLAB and use it to develop the basic simulation model

URL: https://www.yaniklab.science/ucsc

ELE-05: Autonomous Systems, Electrical and Computer Engineeringt Marketplace

Primary Mentor: Haitham Alsaade (he/him)

Number of Interns: 6

Project Description: Autonomous systems have efficiently supported the transportation of either a ground vehicle or an unmanned aerial vehicle (UAV). In particular, Autonomous Ground Vehicle Navigation in Unstructured Environments. One of the most essential takes is when the ground vehicle in Unstructured Environments with dense trees and changing terrain goes up and down, sometimes losing the navigation system signal. The objective of this research project is to substantially enhance mapping and localization identification via a comprehensive learning-based framework leveraging lidar, depth camera, MIDG II, etc..

Tasks: 1- Gain knowledge about autonomous systems and mechatronics.
2- Learn about the main parts of the autonomous ground vehicle, such as electric circuit learning, mechanical learning, and Python software learning.
3- Design a small robot with Python software.
4- Develop the small robot and do a simulation by Rviz and Gazebo.
5- Develop the skills to connect the software and hardware to drive the robot.”

ELE-06: Power electronics Converters in Renewable Energy Microgrids

Primary Mentor: Saeed Aliamooei Lakeh (he/him)

Number of Interns: 4

Project Description: “As renewable energy sources like solar and wind become increasingly integral to our power systems, the role of microgrids in enhancing grid resilience and sustainability is becoming more critical. Microgrids, localized energy grids that can operate independently or in conjunction with the main power grid, are pivotal in integrating renewable energies. This proposal expands on the conventional microgrid framework by integrating advanced circuit technologies and DC/DC converters to optimize the energy management and efficiency of these systems. Microgrids enhance energy security and operational efficiency, particularly in integrating fluctuating renewable energies. To further improve their performance and interaction with electric vehicles (EVs), this proposal suggests the incorporation of sophisticated circuit designs and DC/DC conversion technology. These elements are crucial for refining the flow and storage of energy within the microgrid, ensuring stability amid variable renewable energy production. The integration of circuit technology and DC/DC converters is expected to significantly enhance the operational efficiency and stability of DC microgrids. This approach not only maximizes the utilization of renewable energy but also improves the overall sustainability and resilience of the power infrastructure.
DC/DC converters circuit and control Systems for Microgrids: for efficient energy conversion
Development of advanced circuit configurations tailored for renewable energy integration.
Integration of DC/DC converters to improve the voltage regulation and power quality within microgrids.
Design and simulation of control systems that leverage circuit enhancements and DC/DC conversion to manage energy distribution and stability.
Developing algorithms that optimize the charging and discharging cycles of electric vehicles within the microgrid framework.
Utilizing advanced simulation tools to model the behavior of microgrids with integrated circuit technology and DC/DC converters.
Evaluating the performance and resilience of microgrids under various operational scenarios to optimize energy distribution strategies.

Tasks: Interns will design and simulate DC/DC converters for renewable energy microgrids, develop basic control strategies, and integrate electric vehicle charging models. Using tools like MATLAB/Simulink, they will evaluate system performance and present their findings in a final report and presentation.

ELE-07: Semantic Communication

Primary Mentor: Parisa Oftadeh (she/her)

Number of Interns: 3

Project Description: We are working on one aspect of the future wireless communication systems. Semantic Communication is the study of how to transmit the meaning behind a message from the transmitter to the receiver, rather than focusing on transmitting the exact message. A simple example of this is how humans communicate. Imagine you want to tell your friend that you’re feeling cold. Instead of sending a long, exact sentence like ‘The temperature is low, and I feel uncomfortable,’ you could just say, ‘I’m freezing!’ Your friend understands the meaning without needing every word spelled out. Similarly, in semantic communication, instead of transmitting every bit of data exactly, we focus on conveying the essential meaning, reducing the amount of data sent while maintaining understanding. The benefit of this research is that we can transmit larger amounts of information with a lower bit rate and higher efficiency.

Tasks: Review and summarize research papers: Read state-of-the-art papers and provide a summary, explaining the main ideas and key results in a clear and concise manner.
Algorithm development and implementation: Assist in developing algorithms and reproducing research results, with a particular focus on implementation using Python.

URL: https://campusdirectory.ucsc.edu/cd_detail?uid=zrezki

Film and Digital Media (FDM)

FDM-01: Digital Native Storytelling

Primary Mentor: Matte Hewitt (they/them)

Number of Interns: 3

Project Description: This research project is well-suited for students interested in social documentation, digital media creation, oral history, and visual storytelling. During the summer, SIP interns will become familiar with tools to transcribe and analyze interviews as well as record and edit audiovisual material. Interns will also learn how to conduct fieldwork with curiosity and cultural sensitivity. By engaging with a local Mutsun-Ohlone Tribal Chair, along with readings and documentaries, SIP interns will become familiar with Indigenous storytelling and protocols. They will develop “deep listening” skills and an understanding of the First Peoples of Monterey Bay. The outcome of this project will be a collection of digital media that will call attention to the importance of ancestral wisdom and Indigenous land rights.

Tasks: For the first two weeks of the program, interns will learn about oral history and Indigenous storytelling by watching documentary films and reading a collection of conversations in “We Are The Middle of Forever: Indigenous Voices From Turtle Island on the Changing Earth,” co-written by Dahr Jamail and Stan Rushworth. During independent working time, interns will transcribe previously recorded interviews, drawing quotes and concepts that could be expanded on. Interns will then develop their own research interests based on these transcriptions and work closely with their mentor to develop a plan for one day of fieldwork, which will involve visiting Indian Canyon in the Gavilan mountain range. Interns will use their phones to document the experience through photos, videos, and audio recordings to create a digital media piece integrating everything they’ve learned. Together, the interns’ projects will become part of an online collection of short videos about Indian Canyon. No previous experience in filmmaking or interviewing is required, though interns with an interest in documentary filmmaking and critical content creation are especially encouraged to apply.

URL: https://campusdirectory.ucsc.edu/cd_detail?uid=mshewitt

History of Consciousness (HIS)

HIS-01: Analyzing the Tagalog-Spanish Archive of the Cofradía de San José

Primary Mentor: Philip Conklin (he/him)

Number of Interns: 3

Project Description: We will be assessing the archival records related to the Cofradía de San José, a Filipino Catholic movement that was violently suppressed by the Spanish colonial state in 1841. Popular religious movements like the Cofradía comprise the primary form of people’s resistance to power and domination throughout history. The Cofradía offers a rich site for study because of the related archival materials that have survived: the group’s own hand-written Tagalog letters, fragments of mystical Catholic literature, Spanish bureaucratic documents detailing surveillance and suppression of the group, and so on. I have gathered these digitized materials from the National Archive of the Philippines, and our task will be to catalogue, process, and begin analyzing these documents and see what they can tell us about this important historical event.

Tasks:

Cataloguing digitized archival documents. Identifying and logging author, date, language, and other basic information of specific documents.
Document analysis: use of our own language skills (whatever they may be) as well as AI large language models to transcribe and translate documents in order to assess a document’s audience and purpose.
Macro-level archival analysis: zooming out from individual documents to this archival collection as a whole, we will assess the overall composition of the archive in order to begin to understand what this collection of documents tells us about the nature and priorities of the Spanish colonial state at this moment of history.
Weekly readings and discussion on this particular period of history, as well as on historical research methods and the production of historical knowledge.”

URL: https://histcon.ucsc.edu/graduate/grad-directory.php?uid=pconklin

Latin American & Latino Studies (LAL)

LAL-01: Oral, Digital and Material Histories of Colombian Surfing

Primary Mentor: Brianne Cotter (she/her)

Number of Interns: 3

Project Description: This project analyzes the patterns, images, tropes, references, political currents, economic trends, surfers, and sponsors that characterize the popularization of surfing and surf history in Colombia. This research draws from surf media (e.g., Instagram reels, tourism websites, recorded interviews, surf and travel magazines, YouTube surfing compilations, etc.) to understand the political, economic, social, cultural, and ecological factors that led to surf’s expansion across the Pacific and Caribbean coasts of Colombia. Studying the surf cultures and industries of Colombia reveals the power dynamics shaping tourism, mass media, consumption, leisure, and beach access across the Americas.

Tasks: Interns will perform digital media research and transcription. We will work with a range of sources, including YouTube videos (e.g., surfing compilations, travel vlogs, tourist reviews), tourism sites (e.g., Booking.com, Airbnb, Hostelworld.com), online surf magazine articles (e.g., Surfer Magazine, Surfer’s Journal, Surfline) and other media. Interns will summarize sources, cite relevant material, and analyze material for relevant subthemes of interest (e.g., tourism, infrastructure, geography, industry, conservation, race, class, gender, sexuality, ability, and nationalism). We will pay special attention to the Instagram page of @elpalosurfinterviews, a vlogger who hosts weekly interviews with Colombian surfers. Interns may transcribe limited sections of these recorded interviews, analyzing the content for relevant themes, references, and people.

URL: https://lals.ucsc.edu/graduate/grad-directory.php?uid=brcotter

LAL-02: Queer Latinidades: Cuban American Migrations, Musics, and Drag Performances

Primary Mentor: Jen N Gottlieb (they/them)

Number of Interns: 3

Project Description: Queer Latinidades: Cuban American Migrations, Musics, and Drag Performances

Tasks: Tasks include gathering data online from a variety of sources such as Cuban American news sources, Cuban blogs, CubaCuir data base, as well as social media accounts of nightclubs which have Latine drag nights or regular Latine drag performers, and the social media accounts of Latine drag performers and performances. Essentially students will be given different categories to find data online, which include use of Youtube, Instagram, TikTok (pending availability), news webpages, and other online archives like that of University of Miami’s Cuban Heritage collection.

URL: https://lals.ucsc.edu/graduate/grad-directory.php?uid=jngottli

LAL-03: COLLECTING AND DISPLAYING. THE POLITICS AND POETICS OF ARCHIVING LATIN/X AMERICAN FASHION

Primary mentor: Edward Salazar Celis (he/him)

Number of interns: 3

Project description: Fashioning the body is an activity that all humans engage in. We dress ourselves every day, often expressing our feelings, beliefs, and cultural identities through what we wear. My project investigates Latinx and Latin American dress and fashion in museums, as well as in artistic and design practices across the Americas. I aim to map how the clothing of diverse groups is represented in these contexts. The study of Latinx and Latin American fashion remains limited, so I am excited to contribute to this growing field while exploring its rich histories and visual narratives. Through this project, I hope students will help create a visual archive of fashion to support my research by exploring online resources from museums, galleries, and archives. This initiative offers an opportunity to delve into the captivating world of Latinx and Latin American dress, fashion, and bodily adornment as powerful forms of cultural expression.

Tasks: Interns will explore online museums, galleries, and archives to find images and information related to Latinx and Latin American dress, fashion, and artworks that engage with fashion. They will also complement this research by gathering information from media outlets, newspapers, and other digital sources to identify relevant content about Latinx dress in these contexts. Interns will assist in organizing, classifying, and describing these materials according to the research guidelines provided by the mentor.

URL: https://lals.ucsc.edu/graduate/grad-directory.php?uid=edfsalaz

LAL-04: The Latino Far-Right on Social Media

Primary mentor: Stephanie Shugert (she/her)

Number of interns: 4

Project description: This project analyzes Latino political far-right trends in the 2024 US election. This research is specifically interested in analyzing far-right Latino content on social media, like Reddit, TikTok, Instagram, Threads, X (Twitter), and YouTube. Content includes political news videos, reels, memes, original posts, and comment sections. The goal of this project is to understand the social, cultural, political, and economic factors that push Latinos to join the far-right movement in the US. This research is interested in providing a discourse analysis of contemporary Latinos by observing their social media engagement.

Tasks: Interns will be tasked with finding and collecting research materials related to my project on social media. We will work on finding relevant social media accounts (e.g. Latinos for Trump or conservative Latino pages) and looking through their posts/uploads. Interns will help summarize sources (posts), cite relevant material, and analyze material for relevant subthemes of interest (e.g. immigration/immigrants, economy, race/racism, gender, sexuality, class, nationalism, patriarchy). I will provide interns with a starting list of social media accounts, including that of Bianca Gracia, a Mexican-American conservative Texas politician. Interns will be asked to help transcribe audio from videos on the accounts observed.

Linguistics (LIN)

LIN-01: Listeners Adapt Speech Based on Talker Social Status: Evidence from Pakistani Punjabi

Primary Mentor: Jonathan C Paramore

Number of Interns: 3

Project Description: Linguistics is the scientific study of human language. Many linguists collect data from understudied languages to better understand how languages vary and what they share in common. My research focuses on how people mentally store the words they know — not just their abstract structures, but also their detailed pronunciations and social associations. In a planned experiment, this project will test whether speakers of two Pakistani languages – Mankiyali and Punjabi – subtly imitate the speech of people they hear — and whether they do so more when the speaker has a higher social status. This work explores how language connects sound, memory, and social prestige in human memory.

Tasks:

Literature review of relevant concepts
Experimental design of perception experiment
Generation/development of experiment stimuli for use in the experiment
Conduct pilot experiment on 1-3 native speakers of Punjabi.

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

LIN-02: The Structure of Verbs and Their Arguments in “Altaic” Languages

Primary Mentor: Niko Webster (he/him)

Number of Interns: 3

Project Description: Linguists theorize that the core purpose of verbs is to describe events that occur in the world. In Korean, there are specific, recognizable markings that can be added to any native verb. The language also includes, however, many words that were borrowed from Chinese languages long ago. Even though almost all of these loans have meanings that are synonymous to native Korean verbs, they cannot combine with any native affixes typically available. The project will investigate languages that have some similar properties to Korean, and identify verbs and loanwords in these languages to compare with the observations on Korean. We will consider Hindi and Turkish, though perhaps other languages will also be of interest. Interns will learn basic approaches to syntax, how to utilize language grammars in syntactic research, how to create glosses of linguistic data, and how to make empirical generalizations based on data patterns they discover.

Tasks: As an Intern in this project, you will:

Gain exposure to core theories in the field of syntax through small lectures and problem sets.
Read, interpret, and appraise linguistic grammars.
Practice combing written sources for linguistic data.
Learn the standard linguistic practice for glossing data examples
Collect relevant data from text and annotate using standard glossing
Learn and practice essentials for the presentation of linguistic data in LaTeX, a document formatting software (can be used through the online platform Overleaf, no downloads required)
Learn and execute the basics of making an empirical generalization
Organize and present their findings regularly in a small lab group context

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

LIN-03: Ellipsis Investigations in “Altaic” Languages

Primary Mentor: Sebahat Yagmur Kiper (she/her)

Number of Interns: 3

Project Description: Have you ever known exactly what someone meant, even when they didn’t finish their sentence? That’s what I study! In everyday conversation, people often leave words unsaid, and yet listeners still understand the full message. This phenomenon is called ellipsis. For example, if someone says “Someone left. Guess who?”, you probably understand they mean “Guess who left?”—even though the rest of the sentence is missing. I’m exploring how this works in different languages like Turkish, Korean, Mongolian, and Kazakh. Unlike English, these languages attach small endings—called suffixes—to their question words (e.g., who), which can give important clues about what’s left out, unspoken. By studying how speakers of these languages interpret these incomplete questions, I aim to uncover broader patterns in how humans interpret language, even when it’s fragmentary. This summer, I’ll be working with real data from these languages and find out how they solve this puzzle. My goal is to show how language allows us to say more with less—and how people rely on clues to understand complex structures.

Tasks: As an intern on this project, you will:

Gain exposure to foundational theories in syntax—the study of sentence structure
Read, interpret, and critically evaluate linguistic descriptions (grammars) of lesser-studied languages
Practice extracting linguistic data from written sources
Learn the standard conventions for glossing examples—breaking down word structure and meaning
Annotate and organize linguistic data using these glossing standards
Get hands-on experience with LaTeX, a professional document formatting tool (easily accessible through Overleaf, no installation needed)
Learn how to make and test empirical generalizations based on real linguistic data
Share your progress and findings in a collaborative lab group environment

URL: https://yagmurkiper.github.io

Literature (LIT)

LIT-01: Literary Legacies and Alternate Afterlives in Bungo Stray Dogs

Primary Mentor: Zoë Sprott (they/them)

Number of Interns: 4

Project Description: This summer, dive into Kafka Asagiri’s rich world of Bungo Stray Dogs, a manga and anime series that features characters based on significant literary figures. The goal of this project is to analyze the network of literary legacies and alternate afterlives in the text and to consider the ethics of adapting real people into fictional characters. Working closely with their mentor, interns will have the opportunity to research the real authors alongside their fictionalized characters and to explore particular aspects of Bungo Stray Dogs, such as gender, genre, fashion, textuality, and (in)humanity.

Tasks: For the first three weeks of the program, the interns will watch the series alongside their mentor and hold discussions while watching. During independent working time, interns will compile reflection notebooks, effectively conducting close reading, outlining the research process, and developing their own research interests. As the program progresses, interns will develop their own research interests related to the series, and work closely with their mentor to develop a research plan that will entail close reading, historicization and contextualization, and a robust theoretical framework. No language fluency outside of English is required, but Japanese language learners are especially encouraged to apply.

URL: https://campusdirectory.ucsc.edu/cd_detail?uid=zsprott

LIT-02: Science Fiction and Robots: Rethinking Our Relationships to Technology through Iron Man, Oppenheimer, and Martha Wells’ Murderbot Diaries *TSIP

Primary Mentor: Caitlin-Anne Flaws (she/her)

Number of Interns: 4

Project Description: This summer, watch Oppenheimer, Iron Man, and read Martha Wells’ Murderbot Diaries book series to evaluate and address the history and current roles technology has within our everyday lives. The goal of this project is for interns to focus on and complicate the following questions: Who is technology for? How does it relate to my life? What might enable technological innovation? What is the future of technology? What is a robot? This project will introduce interns to cross-disciplinary materials taken from literature, history, sociology, film studies, and philosophy, and introduce them to the principles of design justice and inclusive design.

Tasks: For the first two weeks of the program, interns will watch Oppenheimer and Iron Man alongside their mentor and hold discussions while watching. The remaining weeks will be spent reading the first 5 books in Martha Wells’ Murderbot Diaries. During independent working time, interns will compile reflection entries in a notebook, conducting close reading, outlining the research process, and developing their own research interests related to technology. As the program progresses, interns will develop their own research interests related to the films and books and work closely with their mentor to develop a research plan that will entail close reading, historicization and contextualization, and a robust theoretical framework. No language fluency outside of English is required.

LIT-03: How to Survive the End of the World: Applied Research and Creative Writing

Primary Mentor: Ocean A Noah (they/them)

Number of Interns: 3

Project Description: This summer, students will select a natural disaster or doomsday event and develop the ultimate survival plan. Options include the Y2K crash, Hurricane Katrina, the Great San Francisco Earthquake, religious Armageddon, 9/11, and more. Unlike traditional research, which relies on peer-reviewed articles and verified sources, creative writing research encourages students to draw inspiration from a wide range of materials. With guidance from their mentor, students will explore documentaries, books, blog posts, and other sources to examine both the facts and fictions of survival narratives.

Tasks: Interns will spend the first few weeks deeply researching a natural disaster or doomsday event, drawing from memoirs, historical accounts, blog posts, and documentaries. During this phase, they will keep a research journal to track patterns, compare genres, and note connections between their own topics and those of their peers. The goal is to understand the lived experience as fully as possible. What was life like before, during, and after the disaster? What were people afraid of? Who, or what, did they hold responsible?

Interns will brainstorm a creative solution to a problem caused by the disaster. Their survival plans can incorporate real-life mechanics or imaginative, science fiction-inspired technology. Each presentation will include a short story featuring a character using their solution, or a drawing or blueprint of the design. Alongside their fiction or artwork, interns will write an introduction that explains the historical context and real-life stories they explored to inspire their project.

LIT-04: Literary Epiphany: Revelation Across Global Traditions

Primary Mentor: Shane Baker (he/him)

Number of Interns: 4

Project Description: Have you ever experienced a moment of sudden understanding, a kind “ah ha!” moment when something about yourself, the world, or time unexpectedly becomes clear? Then you’ve had an EPIPHANY! But did you know the word “epiphany” was coined by a famous modern author, James Joyce? It just so happens that narrating such special moments, when we suddenly gain new knowledge, almost as if some divine spirit planted it in our minds, became a popular trend in twentieth-century literature. In the past, such moments were referred to as “revelation,” a religious word denoting what was understood to be a religious phenomenon. However, as the influence of religious institutions waned in the modern era, the emerging field of psychology stepped in to fill some of the void, which modern authors like Joyce noticed. The question for many people in the modern West then became: From a secular or scientific point of view, how do we honor and make sense of such experiences? Of course, in our own century, we know that religion is not going anywhere, and “secularization” is not just a historical process that happened in the Western world.

I am writing a journal article about the concept of “literary epiphany,” and you’re going to help me! I’m interested in exploring a couple of big questions: When is the distinction between religious and secular helpful, and when does it blind us the richness of certain events? How do Western and non-Western literary traditions contribute to our understanding of the process of secularization? Can literary epiphany tell us something about the future of religious belief and practice? What new pathways of research might we open up between literary studies and (neuro)psychology by studying the way writers write––and readers read––moments of epiphany?

Tasks: Interns will:

Search for and aggregate the appearance of epiphanic moments in various texts by utilizing the library database, 2) learn how to write a summary (“précis”) of research findings, 4) read and discuss many selections from literary and some non-literary texts that narrate epiphanies.
You are not an innocent bystander! Your mentor is writing an article for a peer-reviewed journal, and intern tasks are designed so that you will be helping your mentor complete his article. This is not a drill; this is real research!
Research tasks will take place within the normal internship day schedule. However, if there are special events or other programmatic activities, interns will be encouraged to attend these to get a feel for the SIP as a whole.

URL: https://bulletin.hds.harvard.edu/the-trouble-with-oneness/

LIT-05: Catullus’ Love Poetry: Subtleties in Translation and Their Effects

Primary Mentor: Lena Minh Thai (she/her)

Number of Interns: 3

Project Description: Gaius Valerius Catullus, commonly referred to as just Catullus, was a Latin neoteric poet whose works continue to serve as teaching tools to aspiring Latin language learners 2000+ years later. Catullus’ poems are accessible, engaging, and most importantly, personal and relatable. Catullus’ corpus was definitely diverse in tone and topic. Offensively childish at times and deeply wistful at others, his works attends to all aspects of life and all its antitheses: love and betrayal, courtesy and obscenity, friendships and pettiness, seriousness and frivolity. As a young adult, Catullus also wrote about the joys and sorrows of life at that age as well: from kissing a lover to the loss of a loved one to the apparent theft of a beloved napkin a friend gave to him to vocational passions, Catullus’ poetry was deeply felt, whether it be aggrieved indignance or agonized infatuation. This project aims to begin Latin language learning to explore the nuances and subtleties in Catullus’ writing alongside the application of Translation Theory. Familiarity with the Latin language is not required, and interns will work with a copy of the poems in English.

Tasks: Interns will maintain a notebook for weekly translations. Independently and with the mentor, interns will prepare translations of poems weekly. Interns will read supplementary texts about Catullus and his time period. Interns will learn about and apply Translation Theory. Interns will keep a Commonplace Log.

URL: https://literature.ucsc.edu/graduate/current-students/grad-student-directory.php?uid=lmthai

Microbiology and Environmental Toxicology (MET)

MET-01: Effects of antenatal immune status on maternal gut microbiome

Primary Mentor: Ziaur(Zia) Rahman (he/him)

Number of Interns: 3

Project Description: In rural Bangladesh, pregnant mothers frequently encounter stress, inadequate nutrition, infections, and limited access to healthcare, all of which can negatively impact their health and the development of their children. This research investigates the relationship between immune status and gut bacteria during pregnancy. We utilize data from the (water, sanitation, and hygiene) WASH Benefits Bangladesh (WASHB) study, which tracked pregnant women and their children in low-resource environments. We focus on determining whether specific immune markers influence the composition of gut bacteria during pregnancy.

Tasks: Interns will engage in key aspects of public health and microbiology research, including conducting literature reviews and supporting the development of data analysis plans. They will assist their mentor in critically identifying relevant variables and selecting appropriate data analysis techniques. Interns will also contribute to the early stages of manuscript development by helping to outline the structure of a scientific paper. This experience will offer hands-on learning in epidemiological research methods, critical thinking, and scientific communication. It is ideal for students interested in developing practical research skills and gaining insight into the full process of academic research and publication.

URL: https://audrielin.com/

MET-02 has been re-labeled as CHE-06

MET-03: Child micronutrient status and telomere length in rural Bangladeshi children

Primary Mentor: Sumukh Cadpakar (he/him)

Number of Interns: 3

Project Description: This project is for students passionate about global health and the use of statistical analysis tools to advance policy decisions to support vulnerable communities!
Telomeres are the protective caps at the ends of our chromosomes that protect our genetic code. The length of telomeres has been associated with various diseases and early mortality. Specifically, newborn children are highly susceptible to changes in their genomic structure due to a variety of environmental factors. Our project will analyze how nutrient deficiencies, micronutrients, cause changes in telomere length, leading to potential dangers to health and disease. Our project analyzes experimental data from a global health initiative (WASH Benefits) in rural Bangladesh. Students will be able to conduct a literature review, conduct statistical analysis using R software, and work on developing a manuscript. This project will advance efforts to conduct statistical analysis for a final paper to be published with the discovered findings.

Tasks: The interns will be involved with literature review, data cleaning, data analysis, statistical analysis, helping their mentor in the interpretation of results, creating figures and tables, and outlining a scientific manuscript.

Students will need a computer with the ability to download R statistical analysis software and Zotero for literature management.

URL: https://audrielin.com/

MET-04: Micronutrient Status and Microbiome Diversity & “Nutritional Status and EED *TSIP

Primary Mentor: Nick J Medina (he/him)

Number of Interns: 4

Project Description: Project Micronutrient Status and Microbiome Diversity aims to better understand how micronutrient deficiency and change the gut microbiome of children from rural Bangladesh. Project Nutritional Status and EED objective is to better understand how nutrient status and influence environmental enteric dysfunction.

Tasks: The interns will be involved with data cleaning, creation of a data dictionary, developing a statistical analysis plan, performing analyses in R, table and figure creation, weekly paper review/discussion.

Molecular, Cell and Developmental Biology (MCD)

MCD-01: Validation of Transcriptional Expression in a THP1 Modified Cell Line

Primary Mentor: Jillian Ward (she/her)

Number of Interns: 3

Project Description: According to the American Cancer Society, 1 in 4 children with leukemia have acute myeloid leukemia (AML) which occurs when myeloid cells like monocytes over-proliferate. Although long non-coding RNAs (lncRNAs) make up the largest portion of the human transcriptome, most of their functional roles remain unknown. At the Carpenter lab, we focus on investigating the role of lncRNAs in monocyte and macrophage biology. We
have successfully identified a novel growth suppressor lncRNA, linc02642, in the acute monocytic leukemia cell line, THP1. Knocking down linc02642
using CRISPR interference (CRISPRi), leads to changes in biological pathways involved in cell development, metabolism, and proliferation. The aim of this project is to validate transcriptional expression changes of these genes. Students will learn how to use the UCSC Genome Browser to design
primers, extract RNA from THP1 cells to do qPCR, followed by primer validation by running gels and sending out products for sequencing.

Tasks: Throughout the summer SIP interns will learn how to use the UCSC Genome Browser to design a primer for a specific gene. They will then extract transcriptional RNA from THP1 cells and then create complementary DNA for their gene of focus. The complementary DNA and designed primers will be used to run qPCRs to amplify their gene of interest. With the gene amplified SIP interns will run a gel electrophoresis experiment to visualize their amplified gene. Finally, after running the gel SIP interns will preform a gel extraction and send the extraction out for sequencing to validate that the designed primers are amplifying the correct gene.

URL: https://sites.google.com/a/ucsc.edu/carpenter-lab/home?authuser=0

MCD-02: Using Genetic Mouse Models to Determine GAPLINC’s role in Regulating Immunity

Primary Mentor: Alexa Juliana Mozqueda (she/her)

Number of Interns: 3

Project Description: Sepsis is a life threatening condition resulting from a dysregulated immune response to a pathogen. GAPLINC is a long non-coding RNA that has a regulatory role in mediating our immune response to a pathogen. We’ve identified GAPLINC as a conserved gene between humans and mice that is highly expressed in important cells of the immune system called macrophages. Upon inflammatory activation of macrophages GAPLINC is significantly reduced. We will focus on researching key genes in order to better understand GAPLINCs mechanism in inflammatory pathways. We hope to gain further insight into the ways GAPLINC functions during sepsis, with our long term goal of finding new druggable targets for the treatment of this devastating condition.

Tasks: SIP interns will learn to do quantitative PCR to analyze expression of genes from different mice genotypes. The interns will learn how to analyze scientific papers and conduct experiments. We will use learning tools like the UCSC Genome browser to design primers for our genes of interest. Additionally, gaining wet lab experience such as pipetting, qPCR, and general lab practices.

URL: https://sites.google.com/a/ucsc.edu/carpenter-lab/

MCD-03: Investigating Wolbachia Gene Effects in Yeast

Primary Mentor: Shanene Marleisa Reeves (she/her)

Number of Interns: 3

Project Description: Wolbachia is a bacterium that infects about two-thirds of insect species and some parasitic worms. It has unique effects on its hosts—for example, it suppresses the transmission of harmful viruses like dengue and Zika by mosquitoes. We’re trying to figure out which Wolbachia genes are responsible for these effects. Wolbachia lives inside host cells and is passed from mother to offspring through eggs, making it hard to study since it can’t grow outside its host. Although Wolbachia is naturally found in fruit flies, the effect of a single gene is easier to visualize in yeast. You’ll help us insert Wolbachia genes into yeast and observe how these genes affect the shapes and structures of organelles in yeast. Genes that cause interesting changes will be tested in fruit flies in the future.

Tasks: We hypothesize that the proteins Wolbachia interact with in host cells are highly conserved through evolution and are therefore also found in yeast. This leads us to propose that if we force yeast cells to make certain Wolbachia proteins (especially ones that are necessary for Wolbachia’s survival in its hosts), those proteins will interfere with yeast cell biology. To test this, we’ll insert individual Wolbachia genes into special circular pieces of DNA called plasmids, then put these plasmids into yeast cells and watch how the yeast behaves. If the Wolbachia genes interfere with the yeast’s normal functions, we should be able to see differences in growth. We’ll also use fluorescent microscopy to see if the yeast’s organelles change shape. Over the summer, you’ll learn basic cell biology, lab techniques, and how research works in a biology lab! No equipment, laptop, or prior experience needed (just something to join the Week 1 virtual meetings).

URL: https://mcd.ucsc.edu/faculty/hartzog.html

MCD-04: Elucidating the structure of the Ascaris trans-spliceosome

Primary Mentor: Tiego Gabriel Veramendi Logan (he/him)

Number of Interns: 3

Project Description: Numerous parasites that infect humans and livestock require a distinctive method of pre-mRNA processing, termed trans-splicing, for the accurate expression of their genes. Despite the centrality of trans-splicing to parasite gene expression, the mechanistic basis of this process is poorly understood. The primary objective of this research project is to elucidate the structure of the trans-spliceosome components through the utilization of quantitative PCR and Cryo Electron-Microscopy. Characterising the structure of the SLRNP and trans-spliceosome will enable the development of novel, parasite-specific therapeutics.

Tasks: Interns will learn to purify nucleic acids and protein-RNA complexes. Students will use quantitative PCR to characterize components of the nematode spliceosome.

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

Music (MUS)

MUS-01: Microtonality, Rhythmic Cycles, and Instrumental Systems in Iranian Music: An Introduction to Non-Western Musical Structures

Primary Mentor: Siamak Barghi(he/him)

Number of Interns: 5

Project Description: This project introduces high school students to the core structures of Iranian music, offering a unique perspective beyond Western musical theory. Students will explore microtonal scales and tetrachords—intervals not found in Western tuning systems—through guided listening and vocal exercises. They’ll also study historical rhythmic cycles from the Middle East using hand percussion and vocalization. In addition, students will help transcribe and write musical scores for several original compositions, gaining hands-on experience in music notation. Each student will score multiple pieces, contributing to a creative, collaborative outcome that deepens their understanding of global music and cross-cultural musical literacy.

Tasks: Interns will actively engage in group and individual activities focused on Non-Western music, particularly Iranian music theory. They will explore microtonal scales and intervals not found in Western music, learning to identify and sing these unique tonalities. Interns will study historical rhythmic cycles from the Middle East, performing rhythms vocally and with body percussion. They will also examine the organology of Iranian music through instrument classification and analysis. In addition, interns will support the creation of musical scores for several compositions by transcribing and notating music. Each student will help score multiple pieces, contributing directly to the project’s creative output.

URL: https://campusdirectory.ucsc.edu/cd_detail?uid=sbarghi

MUS-02: Exploration of Music’s Influence on Film Narrative *TSIP

Primary Mentor: Nina Barzegar(she/her)

Number of Interns: 3

Project Description: This project explores the impact of music on film narrative. The mentorship aims to deepen interns’ understanding and empower them to create impactful sonic designs for one-minute videos, whether original videos or selected scenes from existing films. Throughout the project, interns will learn composition techniques, software (Logic Pro) proficiency, and sound editing, emphasizing how sonic elements contribute to the overall narrative and audience experience. Collaborative discussions and exercises will support interns to experiment and refine their designs. Ultimately, interns will apply their acquired knowledge and analytical skills to create music and sonic designs for short videos.

Tasks: Exploring concepts of music, films, and storytelling through various examples. Creating or selecting short videos for their project. Learning the fundamentals of film music composition, including understanding the influence of harmony and instrumentation on film music. Acquiring basic proficiency in Logic Pro, a music software designed for Mac systems. Crafting their music and sound project using Logic Pro, integrating video and sound components. Presenting their finalized video projects.

MUS-03: Analyzing and Creating Afrobeats Music of Nigeria

Primary Mentor: Kolawole Rasheed (he/him)

Number of Interns: 5

Project Description: This research project explores Afrobeats, a popular Nigerian music genre. It involves closely listening to and analyzing songs from the genre’s inception to the present day. In addition to identifying musical elements that will help separate the genre into styles, the project also includes creating original music using a music production application to compose tracks within the identified styles. As a result, interns will not only develop analytical skills but also gain proficiency in using the Digital Audio Workstation (DAW) software. By examining these musical characteristics of tonality and chord chordal movements, the project will generate key data to support my research goal of mapping the development of this popular genre.

Tasks: This project will have interns closely listening to some of Nigeria’s best modern music from the 2010s till date. Interns will join me in analyzing a wide array of Afrobeats songs for musical elements like tonality, chord structure, and progressions. By finding common elements in the music, interns will help map the genre’s evolution. Also, interns will work as a team to produce music that exemplifies the distinct Afrobeats styles.

Ocean Sciences (OCS)

OCS-01: Marine particles in the Antarctic: controlling the fate of the micronutrient iron from glacial melt

Primary Mentor: Thao Vy Le (she/her)

Number of Interns: 3

Project Description: Climate change is causing the Antarctic Ice Sheet to melt, as warming ocean waters accelerate ice loss and contribute to global sea level rise. The fasting melting Antarctic glaciers are melting into the Amundsen Sea, which abuts part of the West Antarctic Ice Sheet.This freshwater influx is increasing the supply of iron, a critical micronutrient for the growth of phytoplankton, to the Amundsen sea, and potentially to the broader Southern Ocean, where it could be an influential control on global climate. Whether the glacially-enhanced iron makes it to the Southern Ocean depends on the abundance and type of marine particles in the ocean, which act to trap and remove iron from seawater. Students will contribute to this research by measuring and analyzing the concentrations of particles collected from the Amundsen Sea in 2024 to better predict the fate of glacially-enhanced iron.

Tasks:

Learn lab safety measures

Understand basic principles of chemical oceanography

Measure particulate inorganic carbon (PIC) concentration using the coulometer

Prepare particulate organic carbon (POC) sample for analysis

Analyzing POC results

Learn how to use freely available oceanographic visualization software (Ocean Data View- this is a free software)

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

Philosophy (PHI)

PHI-01: Can Art Be Wrong? Rethinking Justice and Morality Through Aesthetics

Primary Mentor: Vivian Dong (she/her)

Number of Interns: 3

Project Description: This research project invites SIP interns to explore how philosophy can be used as a tool to understand the relationship and intersection between art, ethics, and social justice. Interns will begin with foundational questions such as: What is art? and How should we evaluate its aesthetic value? From there, the project will move into more practical and socially pressing topics, including: Can an artwork or artistic genre be immoral? Is it acceptable to use AI in the creative process? How do unjust social conditions shape artistic expression—and how can art respond to or resist those conditions? To engage with these questions, interns will read and discuss philosophical texts alongside their mentor, drawing from the fields of aesthetics, moral philosophy, and social justice theory. By doing so, interns will begin to build their own reasoning framework for navigating controversial and timely debates at the intersection of art and society.

Tasks: As the project progresses, interns will choose a topic of personal interest or select from mentor-provided prompts, focusing on specific issues such as cultural appropriation, censorship, or AI-generated art. They will then develop this topic into a final research project, which can take the form of a philosophy research paper or a public-facing website. The goal is not only to provide students with hands-on experience in philosophical inquiry but also to support them in producing thoughtful, socially engaged work that raises public awareness of the ethical and political dimensions of art.

URL: https://mostajo-radji.com

Physics (PHY)

PHY-01: Liquid Exfoliation of Two-Dimensional Materials

Primary Mentor: Carlos Gonzalez (he/him)

Number of Interns: 3

Project Description: A new computing architecture has been studied recently to go beyond Moore‚Äôs Law known as neuromorphic computing. One device type that can realize neuromorphic computing is memristor, which mimics the human brain by integrating memory and processing. We will use 2D transition metal dichalcogenides (TMDs) as the semiconductor in these devices. A ‚Äútop-down‚Äù method called liquid phase exfoliation (LPE) will be implemented to fabricate atomically thin TMDs. This technique involves immersing the crystal in a solvent that separates the layers. Compared to the Nobel prize-winning scotch-tape method, LPE has a higher exfoliation yield of atomically thin flakes. Interns will implement this technique to achieve large, atomically thin flakes for use in memristor devices.

Tasks: In this project, interns will be performing hands-on research in the lab to acquire 2D TMD flakes. The purpose is to use these flakes for new devices. The exfoliation technique is new to the lab, so the interns will combine literature research and experimental trial-and-error to achieve a high yield of large, atomically thin flakes. They will work with graduate and undergraduate students to characterize the quality of these flakes with an optical microscope and atomic force microscopy (AFM).

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

PHY-02 In situ TEM study of polar domain dynamics in 2D ferroelectrics

Primary Mentor: Hem Prasad Bhusal (he/him)

Number of Interns: 3

Project Description: Recent research has revealed that ferroelectricity can emerge in non-polar van der Waals materials when their individual layers are stacked in a manner that disrupts inversion symmetry. This phenomenon, known as sliding ferroelectricity, has attracted considerable attention because it offers a new way to introduce ferroelectric properties in a wide range of non-polar 2D materials, opening possibilities for novel electronic applications. In this project, we employ operando transmission electron microscopy (TEM) to investigate how polar domains behave and switch in response to an applied electric field in twisted bilayers of transition metal dichalcogenides (TMDs), such as MoS2 and WS2. To prepare these 2D ferroelectric samples, monolayer TMDs are exfoliated from a bulk crystal and assembled into bilayers using a tear-and-stack approach, creating structures with small twist angles. These bilayers are then encapsulated with multilayer hexagonal boron nitride (hBN) and contacted with top and bottom graphite layers. The completed stack is transferred onto a Protochips electrical e-chip for TEM analysis. This study focuses on studying domain dynamics in ferroelectric 2D heterostructures.

Tasks: This research project is primarily experimental and focuses on preparing samples for transmission electron microscopy (TEM) studies. SIP interns will play a key role in the sample preparation process. Their responsibilities include mechanically exfoliating bulk TMDs, graphite, and hBN using the scotch tape method to obtain monolayer and multilayer flakes. Interns will use optical microscopy to identify flake thickness and size and will also be trained in Atomic Force Microscopy (AFM) to confirm layer numbers. They will then assist in fabricating heterostructures by transferring selected flakes and stamp down them onto a protochip TEM substrate. These prepared samples will be used for in situ TEM investigations of ferroelectric domain dynamics.

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

Psychology (PSY)

PSY-01: The Speed of Change: Collective Future Thinking & Its Role in Political Activism

Primary Mentor: Joshua Rotondo (he/him)

Number of Interns: 3

Project Description: With this study, we hope to understand how one’s imagination of their country’s future relates to their political opinions and behaviors, as well as how their anxiety about their country’s future relates to these same opinions/behaviors. We hypothesize that people who are more anxious about their country’s future will have a harder time imagining their country’s future; similarly we also hypothesize that people who have more ambitious ideas for their country’s future will also have a similar relationship.

Tasks:

1. Reviewing research papers related to the project so we can write a background for the study.

2. Using computer software to analyze and visualize the data collected for the study.

3. Help write the research paper reporting on the study’s data.

PSY-02: Counterfactual Thinking in Collective Memory: How Imagined Past Influences Collective Future

Primary Mentor: Emine Seyma Caglar Kurtulmus (she/her)

Number of Interns: 3

Project Description: When we think about ourselves, we often imagine alternative realities for past events, asking ourselves, “What if I had done this instead?” or “Would the outcome have been different if I had acted differently?” These kinds of thinking are called counterfactual thinking. But what about counterfactual thoughts generated about collective memories? How do these imagined past events affect collective future thinking? This study primarily aims to explore how imagined past events (events that didn’t happen but could have) influence collective future thinking. Specifically, we will investigate how these imagined past events affect agency, temporal distance (subjective distance), level of construal (type of events), and the emotional valence of collective future thoughts.

Tasks:

1. Literature Review‚ Interns will review and summarize existing research on counterfactual thinking and collective temporal thought. Discussions on key articles will provide a deeper understanding of the topic.

2. Data Coding‚ Interns will analyze qualitative data by coding counterfactual content, focusing on agency and emotional valence.

3. Statistical Analysis, Interns will gain experience using Excel and statistical software to analyze coded data, providing insight into data processing and interpretation.

PSY-03: The Effects of Digital Technologies on Cognitive Processes

Primary Mentor: Jexy An Nepangue (she/her)

Number of Interns: 3

Project Description: My research explores how different technologies—such as generative AI, photo-taking, and the internet —affect memory. We often rely on tools like AI chatbots or our phones to store information, but does this change how we learn? Taking photos, for example, might help us capture moments, but does it also make us forget details? By studying how these technologies impact attention, memory, and learning, my work helps us understand when digital tools support memory and when they might hinder it. This research is crucial for improving our learning in a world where technology is everywhere.

Tasks: Interns will gain hands-on experience in psychological research by helping run experiments, reading and discussing scientific articles, and presenting key findings. They will also learn basic data analysis skills with minimal work in R (a statistical programming tool). This is a great opportunity for students curious about how technology affects memory and learning and who want to explore how research is conducted in cognitive psychology. No prior experience is required—just enthusiasm and a willingness to learn! Computation resources needed: Any laptop

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

PSY-04: Hetereogeneity in American Collective Temporal Thought: The Role of Ethnicity, Framing, and Age

Primary Mentor: Zizhan Yao (he/him)

Number of Interns: 3

Project Description: Based on a previously collected American dataset, this project investigates the potential convergence and divergence in American’s social representation of their nation’s past and future. We will look at how different ethnic groups may have varied collective memory and future projections as well as potential age-related difference. In addition to looking at participant’s emotional valence towards collective temporal thought, we will employ network science approach to uncover the embedded narrative structure of each group’s collective representations. Findings will shed light on the complexity of an American idenity and the importance of looking beyond white sample.

Tasks:

-Code textual data based on themes
-Run statistical analysis such as t-tests and ANOVA
-Create R scripts to run network analysis and generate plots
-Read the necessary background readings on psychology, sociology, etc.
-Present research findings in lab settings and research seminars
-Learn to use basic statistical softwares such as SPSS, Jamovi, Jasp, R

PSY-05: False Memory and Social Media

Primary Mentor: Melissa Chen (she/her)

Number of Interns: 3

Project Description: False memories are memories that have been distorted from the original memory due to many factors (e.g., passage of time, suggestibility). This study explores the impact of social media usage on false memories using the Deese-Roediger-Mcdermott (DRM) paradigm. The DRM paradigm has been used widely used by researchers to study false memories. SIP interns will dive in to the literature of false memories to learn about the mechanisms, theories, and how it shows up in applied settings. Interns will also learn how experiments are created ran, and how recall data is analyzed.

Tasks: SIP interns will be conducting literature reviews to gain a better understanding of false memories and how social media may play a role in false memory creations. They will also learn how memory experiments are set up, created, and run on Qualtrics. Interns may also analyze recall data.

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

PSY-06: Perceptual strategies and eye movements in emotion recognition across various levels of autistic traits

Primary Mentor: Golnoosh Soroor (she/her)

Number of Interns: 3

Project Description: In our study, we explore how people detect basic emotions (happiness, sadness, anger, disgust, fear, and surprise) from faces and which perceptual strategies (detail-focused vs. whole face) are more helpful for emotion recognition. We use a priming method (inducing global or local processing) to examine how emotion recognition varies in individuals with different levels of autistic traits. Eye tracking is also used to study eye movement patterns and identify key areas of the face for emotion understanding.
We use MATLAB for data analysis and design tasks using face images and videos. Previous projects analyzed eye movements and emotion recognition with static posed emotional faces, and in the next experiment, we will compare this with dynamic real-life videos to investigate how task design influences performance and eye movement patterns. For instance, real-life videos may elicit avoidance behavior or different eye patterns compared to static faces.
Lastly, we assess how autistic traits affect emotion recognition, eye movement patterns, and attentional preferences, aiming to identify optimal social behaviors tailored to individual needs.

Tasks: Interns will contribute to the project in various ways, including reviewing relevant research papers and assisting with experiment design using videos and pictures of emotional faces. They will be trained to use the eye tracker and may assist with data collection, depending on the project’s progress. Additionally, interns will be involved in data analysis, contributing to this aspect as the project advances. The tasks will evolve based on the project’s timeline, offering opportunities to gain hands-on experience in experiment design, data collection, and analysis.ecall data.

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

PSY-07: A study of Speech Error Monitoring and Non-Invasive Brain Stimulation

Primary Mentor: Nathan Caines

Number of Interns: 4

Project Description: This project is at the intersection of language and cognitive neuroscience, it involves using several techniques such as EEG and non-invasive brain stimulation to better understand the relationship between the brain and its general processes in regards to language production and comprehension. Specifically focused on how we are able to monitor and correct our own speech errors. Work will vitally assist in running and transcribing speech experiments

Tasks:

Will require any laptop with audio
Set-up and maintenance of equipment (like EEG)
Organization filtering of audio files
Transcription of audio files
Classification of speech errors
Research into types of speech errors and EEG methods
assist researcher in running experiments”of tasks, including the following:

URL: https://cognitiveneurosciencelab.ucsc.edu/

PSY-08: Electrophysiological Correlates of Cognitive Control during Naturalistic Language Processing

Primary Mentor: Ashley Rosenfeld (she/her)

Number of Interns: 3

Project Description: This project investigates the underlying neural mechanisms of cognitive control during speech processing using cognitive neuroscience methods to analyze brain activity. SIP interns will work with electroencephalography (EEG) data, which derives from electrical activity from cortical parts of the brain recorded by electrodes placed on the surface of the scalp. The experimenters are primarily interested in analyzing the time-locked event-related potentials (ERPs) and wave oscillations associated with auditory processing and comprehension. Interns will learn how to design and develop a multi-part research project, read and analyze EEG data, recognize neural patterns associated with different cognitive functions, and conduct cognitive neuroscience research at different stages.

Tasks: SIP interns will be assigned a combination of tasks, including the following:

(1) Assisting development of current study design
(2) Shadow experiments and data monitoring
(3) Stimuli creation for multi-part experiment; and (4) literature reviews on related research.

URL: https://sites.google.com/ucsc.edu/boudewynlab