DSI Celebrates 2026 Summer Program Researchers

This summer, 48 undergraduate and high school scholars participated in the UChicago Data Science Institute’s Summer Research Programs — the first cohort hosted in the DSI’s new home, the Lorraine and Yuji Suzuki Center. Over eight weeks, students in Summer Lab and the Data Science for Social Impact (DSSI) programs engaged in hands-on research across 27 projects spanning data science, artificial intelligence, public health, environmental sustainability, and interdisciplinary fields. Along the way, they developed new technical and research skills, collaborated with peers and mentors, and tackled real-world challenges before presenting their findings at the DSI Summer Research Symposium.  

Summer Lab: Hands-On Research Across Disciplines

Students participating in the Summer Lab are paired with faculty mentors across the university. The program is designed to provide undergraduate and high school students with hands-on experience in data science research, fostering their skills in computational analysis, data management, and interdisciplinary collaboration. Participants engage in cutting-edge projects that address real-world problems, working closely with their faculty mentors and peers. This year, 22 students took on wide-ranging projects, with examples including breast MRI vascular mapping and machine learning (ML)-driven battery development. 

For many, Summer Lab offered their first look into data science research. When asked about her proudest accomplishment, Vardah Khan – a Data Science and Integrated Health Studies double major at the University of Illinois, Chicago – cited learning Python from scratch to complete her research project. “This experience gave me more confidence in my ability to learn new skills and reminded me how much I enjoy research at the intersection of data science and biology,” she said. 

Reflecting on the summer, Dr. Kyle Chard, Research Associate Professor of Computer Science at the University of Chicago and Summer Lab Program Director, shared, “This summer was our most exciting yet. Having almost 50 high school and undergraduate researchers co-located in the new DSI building created an amazing energy and produced genuinely novel research.” As the summer came to a close, students left with new skills, lasting connections, and a deeper understanding of what it means to pursue research.

Learn more about this cohort’s Summer Lab projects here. 

DSSI: Time Series and Multi-Modal Data for Environmental and Public Health

Data Science for Social Impact (DSSI) is a summer research program for undergraduate students who are passionate about pursuing research and data science to make a positive social impact. DSSI includes intensive coursework and applied research training, where students work in teams on data science research projects covering topics such as climate, health, policy, and human rights. Many research projects are sourced among our 11th Hour Project partners. 

DSSI welcomed 26 students, nominated by faculty from 11 partner schools. This year’s research theme, Time Series and Multi-Modal Data Science Applications for Environmental and Public Health, pushed students to work across disparate data types, including longitudinal, geospatial, categorical, and environmental sensor data. DSSI opened with a two-week data science bootcamp, where students build machine learning and coding skills before applying them to real-world problems. For the remaining six weeks, students work in small groups on a social impact data science project, translating their new technical skills into research with tangible community impact.

Dr. Mario Bañuelos, Associate Professor and Associate Chair of Mathematics at California State University, Fresno, led the summer’s research and intellectual direction as the DSSI Research Director. “After the first two weeks of intensive instruction on data science and time-series, students participated in a healing circle and learned about what other students carried with them into the space,” said Dr. Bañuelos. “This, along with the community norms defined at the start of the program, provided a meaningful way for research groups to bring both their lived experiences and computational knowledge in conducting socially impactful and transformative work.”

Learn more about this year’s DSSI projects here.

Building the DSI Summer Community

Students also shared experiences outside of the classroom and research environment. Through intentional programming and community-building, students built connections starting on day one of the program. For example, an art and data visualization workshop challenged students to think creatively about how they told the story of their data, not just what the data found. Students also bonded through DSI summer program traditions like bowling, a Chicago history bus tour, volunteering in Nichols Park, and a picnic at Promontory Point. 

Professional development included a weekly lunch series, where students heard from faculty from across the university and learned about multi-disciplinary, data-driven research. Students also took part in a career workshop hosted by the UChicago Career Advancement Office, a graduate school information session hosted by UChicagoGRAD, and an industry panel featuring data scientists from DSI industry partners.

Sharing Results and Learnings: DSI Summer Research Symposium 

The summer concluded with the DSI Summer Programs Research Symposium, which marked the culmination of eight weeks of intensive research, collaboration, and learning.  Through exploring advances in biomedical health and AI, education, robotics, and physical sciences, students demonstrated the power of data science to generate knowledge and drive meaningful social impact across disciplines. 

For many students, the summer’s real growth happened in the space between the technical work and the people around them. Kalyan Cherukuri, a Summer Lab student and rising senior at Illinois Mathematics and Science Academy, reflected that “my labmates and program cohort pushed me to look beyond the results and think more deeply about what the research process itself could teach me.”

That same spirit of growth through collaboration echoed in City Colleges of Chicago student Hiep Le’s experience with DSSI: “What I valued most was not only strengthening my technical skills, but also learning how to work through challenges, learn from mistakes, and communicate effectively with my team,” an experience Le says built the confidence to keep growing in data science and applied mathematics. 

For Samantha Adorno, a Summer Lab student and computer science major at the University of Kansas, the summer opened an unexpected door: applying data science to neuroscience, a field she knew little about going in. “I really appreciated the flexibility my mentors gave me and got to feel a real sense of ownership over the project,” she said.

Across every project, students left DSI Summer Research Programs with a deeper sense of what it means to do research, and why it matters.

Read on for additional projects.

AniMotion: Hands-on Robot Teaching and Generative Retrieval of Dynamic Movements with TOIO Robots using LLM

Student: Alexandra Preuss (Walter Payton College Preparatory High School)

Preuss worked in Dr. Ken Nakagaki’s lab to record and replay physical movements in TOIO robots. Using AI, movements were translated into programmed execution paths displayed in the software for users to observe the automatic playback of their robot’s movements.

Fusing High-Spatial-Resolution and Ultrafast DCE-MRI Expands Breast Vessel Networks

Student: Sarit Bose (Neuqua Valley High School)

Bose worked under Dr. Anna Woodard to build breast-vessel network inputs from MRI images to feed to a model that predicts if less intensive therapy will be beneficial to a breast cancer patient or recommends an alternative approach to those unlikely to respond to treatment.

Large Language Models for Battery Electrolyte Formulation Discovery

Student: Fife Adeyemo (Texas A&M University)

Adeyemo used data and AI to accelerate the process of building better battery electrolytes by extracting data from existing research papers and turning this data into useful inputs for prediction models. 

Filling in The Gaps: A Multi-Modal Approach to Black Maternal Health 

Students: Lilly Weaver (University of Texas, San Antonio), Peace Amichoh (Prairie View A&M University), Edward Kofi Sie (Howard University), Mali Glemaud-Thesee (Morehouse College), Christyana Walker (Spelman College)

This team collaborated with Jewel of Justice, a Fresno, California-based nonprofit advancing Black maternal justice, to analyze participant feedback from a workshop series and develop refined survey instruments to more effectively evaluate participant outcomes. 

Forecasting California Pesticide Use: Closing the 2-Year Reporting Gap 

Students: Luis Ortiz (California State University, Fresno), Peter Kasomo (Prairie View A&M University), Sodeeq Adeyinka (Chicago State University), Tristan Prathap (City Colleges of Chicago)

To address the two-year delay in pesticide reporting data in California, the team analyzed monthly usage data for 8 active pesticide ingredients across 58 counties from 2017 to 2026, to model and better predict county- and state-wide pesticide use trends.  

Expanding Valley Fever Forecasting In California With Environmental LSTMs 

Students: Sanaa Jain (North Carolina State University), Austin Tathong (California State University, Fresno), Félix Arzola (University of Puerto Rico, Río Piedras), Hiep Le (City Colleges of Chicago)

This team developed county-by-county and aggregated models to showcase how environmental features can provide early warning predictions of Valley Fever, a lung infection which is common in parts of the southwestern US and California.