✅ Eligibility

• Open to undergraduate and Masters students from Prairie View A&M University and Morgan State University
  
• Students should have some coursework or experience in data science, computer science, statistics, or related fields
  
• You don’t need prior research experience—just curiosity, commitment, and willingness to learn

💸 Funding

Interns selected for the program will receive:

• A paid summer research fellowship ($5000 stipend)
  
• Housing and dining on-campus fully covered
  
• Travel costs covered (round trip to UCSD)
  
• Mentorship, networking, and career development opportunities
  
• Field trips to the world-famous San Diego Zoo, beaches, and more!

📅 Timeline

• Applications Due: October 31, 2025 at 11:59pm anywhere on Earth
• Letter of Recommendation Due: November 23, 2025, at 11:59pm anywhere on Earth
• Notification of Acceptance: December 12, 2025
  
• Program Dates: June 21 – August 14, 2025 (tentative)

🧑‍🏫 Mentors & Projects (in alphabetical order)

Alex Cloninger (website)

My research area: Machine learning theory

Link to recent paper(s) that I’m particularly proud of:
Linear optimal transport embedding: provable Wasserstein classification for certain rigid transformations and perturbations
A deep network construction that adapts to intrinsic dimensionality beyond the domain 

In one sentence: what is the main research question this project will answer? How can you determine information about every element in a dataset from only a subset of the data?

In one sentence: how is this project novel? This project will be the first to incorporate multiple mathematical tools into a unified approach.

If this project is wildly successful: We will publish a paper in a top ML conference!

What kinds of work will a summer intern do in your research lab? Develop and implement algorithms, analyze graphs, and run experiments.

In my lab, we find ourselves getting excited about: Building mathematical tools that make algorithms more powerful and efficient.

Haojian Jin (website)

My research area: Human-computer interaction, Data Privacy

Link to recent paper(s) that I’m particularly proud of:
Redesigning Privacy with User Feedback: The Case of Zoom Attendee Attention Tracking 

In one sentence: what is the main research question this project will answer? How can we make privacy risk assessment more accessible and accurate?

In one sentence: how is this project novel? Past work has relied on lengthy free-form assessments—this project makes them simpler and more practical.

If this project is wildly successful: We will release an open-source tool that becomes widely adopted.

What kinds of work will a summer intern do in your research lab? Design and refine multiple-choice questions for privacy assessments, run user studies.

In my lab, we find ourselves getting excited about: Turning complex privacy concepts into simple, understandable tools.

Sam Lau (website)

My research area: Programming and data science education, human-computer interaction

Link to recent paper(s) that I’m particularly proud of:
Ban It Till We Understand It” to “Resistance is Futile”: How University Programming Instructors Plan to Adapt as More Students Use AI Code Generation and Explanation Tools such as ChatGPT and GitHub Copilot
Teaching Data Science by Visualizing Data Table Transformations: Pandas Tutor for Python, Tidy Data Tutor for R, and SQL Tutor 

In one sentence: what is the main research question this project will answer? How can we design and implement an AI Tutor for data science that helps students learn, especially the students who are struggling?

In one sentence: how is this project novel? Large language models are great at solving programming and data science problems, but it’s unknown how to make use of LLMs to help students learn effectively.

If this project is wildly successful: We will deploy an open-source AI tutor across courses at UCSD and publish a paper about its efficacy.

What kinds of work will a summer intern do in your research lab? Hack on a live LLM-based tutoring system, analyze student responses, and conduct user studies with students and instructors.

In my lab, we find ourselves getting excited about: How education is evolving in response to LLMs and eating at the best taco shops in San Diego!

Gal Mishne (website)

My research area: Machine learning, applied math, computational neuroscience

Link to recent paper(s) that I’m particularly proud of:
RATS: Unsupervised manifold learning using low-distortion alignment of tangent spaces
Learning Cartesian Product Graphs with Laplacian Constraints 

In one sentence: what is the main research question this project will answer? How to measure similarity between two (potentially large) graphs?

In one sentence: how is this project novel? We will use machine learning tools to measure graph similarity in a scalable way.

If this project is wildly successful: We will publish a paper in a top ML / neuroscience conference.

What kinds of work will a summer intern do in your research lab? Analysis of large datasets, coding (Python), learning ML methods.

In my lab, we find ourselves getting excited about: Graphs, neural recordings, and ice cream.

Benjamin Smarr (website) 

My research area: Time series in health AI, human-AI health collaboration

Link to recent paper(s) that I’m particularly proud of:
General feature selection technique supporting sex-debiasing in chronic illness algorithms validated using wearable device data
AI for precision medicine must keep non-random complexity in mind to support equity in outcomes 

In one sentence: what is the main research question this project will answer? Can we support decision making informed by health data using AI?

In one sentence: how is this project novel? Tools like this can automate interpretation and provide support to historically underserved groups.

If this project is wildly successful: We will release the product as a tool for both health care providers and individuals.

What kinds of work will a summer intern do in your research lab? Learning about statistical methods for dissecting time series health data.

In my lab, we find ourselves getting excited about: How new data sources empower historically underserved populations.

Duncan Watson-Parris (website)

My research area: Machine Learning for Climate

Link to recent paper(s) that I’m particularly proud of:
ClimateBench v1.0: A Benchmark for Data‐Driven Climate Projections
FaIRGP: A Bayesian Energy Balance Model for Surface Temperatures Emulation

In one sentence: what is the main research question this project will answer? Can we machine learn better climate physics?

In one sentence: how is this project novel? Previous attempts to learn better representations have been limited—this project takes it further.

If this project is wildly successful: We would publish a paper describing the results!

What kinds of work will a summer intern do in your research lab? Build ML models of atmospheric physics, analyze results, and compare with climate models.

In my lab, we find ourselves getting excited about: Thinking about new ways of modeling the Earth!