Brown University Data Science Institute

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Brown University Data Science Institute A hub for research and education in foundational methodologies of data science at Brown University.

Brown's Data Science Initiative operates as a hub, working at the intersections of teams of scholars spanning diverse fields of study to tackle complex problems. At its core, the DSI brings together some of Brown’s strongest academic departments: Mathematics, Applied Mathematics, Computer Science and Biostatistics. Together, researchers across diverse fields will form a vibrant, campus-wide intellectual community, developing innovative methods in data science to answer critical questions in environmental science, neuroscience, particle physics, engineering, public policy, the humanities and elsewhere.

Announcing the Physical AI Summit 2026 at Brown University!SAIR's first East Coast summit is landing in Providence! Co-h...
10/02/2026

Announcing the Physical AI Summit 2026 at Brown University!

SAIR's first East Coast summit is landing in Providence! Co-hosted by the Brown Data Science Institute and the Foundation for Science and AI Research (SAIR), the Physical AI Summit 2026 brings together leading scientists, AI builders, and industry leaders to explore how robotics and physical AI are moving from research labs into real-world systems.

When: Thursday, November 12, 2026
Where: Pembroke Hall 305, Brown University Campus

What’s in store?
- Keynotes by Brown leaders George Karniadakis and George Konidaris.
- Panels featuring Deans and Institute Directors from Harvard, Columbia, Cornell, and Brown.
- Industry perspectives from Bosch AI, Hugging Face, Liquid AI, and more!
- Networking with researchers, entrepreneurs, and investors.

Space is limited! Confirmations are granted on a rolling basis, so make sure to register by November 9th.

Register now: https://sair.foundation/events/physical-ai-summit-2026

Huge news! DSI's Director, Prof. Brenda Rubenstein () has been named a finalist for the 2026 Blavatnik National Awards f...
09/18/2026

Huge news! DSI's Director, Prof. Brenda Rubenstein () has been named a finalist for the 2026 Blavatnik National Awards for Young Scientists in Chemical Sciences!

Her computational methods are making chemistry faster, cheaper, and smaller—pioneering advances from quantum materials to molecular data storage.

Join us in congratulating her on this well-deserved honor!

Can algorithms actively remove societal barriers? Join us Sept 24–26 for the Machine Learning Symposium on Justice in He...
09/08/2026

Can algorithms actively remove societal barriers? Join us Sept 24–26 for the Machine Learning Symposium on Justice in Healthcare, Education, and Public Policy at Brown! Hear from top leaders in AI, social good, and policy. Register now: https://bit.ly/498LOy5

Meet our third new CCMB PhD student: Bohoon ShimBoohoon Shim earned a bachelor's degree in Molecular and Cellular Biolog...
09/03/2026

Meet our third new CCMB PhD student: Bohoon Shim

Boohoon Shim earned a bachelor's degree in Molecular and Cellular Biology with a minor in Computer Science from Johns Hopkins University. Following his undergraduate studies, he worked as a postbaccalaureate researcher at Dana-Farber Cancer Institute in the Catherine Wu Lab, where he contributed to projects evaluating the efficacy of cancer vaccine clinical trials and developing computational methods to identify novel therapeutic targets.

These experiences led Bohoon to pursue research focused on developing computational approaches for discovering therapeutic targets through next-generation sequencing. He is particularly interested in the unannotated genome and transcriptome, especially novel transcripts and peptides arising from transposable element expression and other noncanonical genomic regions. He hopes to better understand how these molecules contribute to disease and whether they can serve as novel antigen targets for immunotherapy.

Originally from South Korea, he is excited to explore the collaborative research environment at CCMB and become part of the Brown community. Outside of research, he enjoys playing golf, soccer and working out.

Meet our second new CCMB PhD student: Junbong JangJunbong Jang is a first-year PhD student in Computational Biology at B...
09/02/2026

Meet our second new CCMB PhD student: Junbong Jang

Junbong Jang is a first-year PhD student in Computational Biology at Brown University. His research focuses on developing interpretable computational models to understand how cellular states evolve during disease progression and in response to perturbations.

Junbong earned his undergraduate degree in Computer Science from Worcester Polytechnic Institute and his master’s degree in Artificial Intelligence from the Korea Advanced Institute of Science and Technology. His previous research includes developing deep learning methods for live-cell segmentation and contour tracking, as well as methods for diagnosing kidney and gallbladder diseases using ultrasound imaging. Before joining Brown, he worked at a surgical robotics startup in South Korea, where he developed computer vision and sensor-fusion technologies to improve surgical precision.

This fall, Junbong will rotate with Professor Ying Ma. He is excited to return to academia and collaborate with the CCMB community, while exploring Rhode Island. Outside of research, he enjoys hiking, cooking, and watching movies.

Meet our new CCMB PhD students: Madeline ReaMadeline Rea is excited to begin her graduate studies as a first-year PhD st...
09/01/2026

Meet our new CCMB PhD students: Madeline Rea

Madeline Rea is excited to begin her graduate studies as a first-year PhD student in the Center for Computational Molecular Biology. She graduated with B.S. degrees in Neuroscience and Data Science from the University of Michigan, along with a minor in Writing.

For her Neuroscience thesis, she developed neuromorphological algorithms in the Kwan Lab and for her Data Science thesis, she reconstructed polygenic risk scores in simulated populations under Professor Terhorst. She also interned in the Munger Lab in Bar Harbor, Maine, as part of the 2024 Jackson Laboratory Summer Student Program cohort.

For her graduate studies, she's interested in examining the intersections between genetic diversity and global health, and will be exploring labs as a CCMB rotation student.

Outside of research, Madeline enjoys making zines, ice skating, playing video games, writing, and is slowly but surely learning to sew.

Summer is still in full swing here at Brown! We found a sunny day this week to gather our students and faculty here duri...
08/06/2026

Summer is still in full swing here at Brown! We found a sunny day this week to gather our students and faculty here during the summer for popsicles and some fun! Thanks everyone who dropped by our summer social!

Campus may be quiet during the summer, but at the Data Science Institute, we're busy reflecting on our year full of impo...
07/07/2026

Campus may be quiet during the summer, but at the Data Science Institute, we're busy reflecting on our year full of important milestones for DSI and planning for a great new year starting in the fall. DSI is proud to continue being an integral center for computational sciences and humanities at Brown through our innovative educational programs, support across campus for data science research, interdisciplinary programming, and dedicated spaces for collaboration.

We can't wait for another great year at the Data Science Institute at Brown!

Alt text:
Highlights from 2025-2026
In the past year, the Data Science Institute has...
- Launched our new Online Master’s in Data Science: Policy, Governance, and Society with an inaugural cohort of 24 students,
- Welcomed new, distinguished faculty members including our new Institute Director, Dr. Brenda Rubenstein, PhD, and Dr. Tomo Lazovich, PhD, JD,
- Awarded more than ten exciting DSI Seed & Collaborative Research Grants to scholars across campus,
- Initiated our new Early-Career Breakthrough Faculty Awards and more than ten Data Science Working Groups, run by students and faculty across the university,
- Co-hosted the first-ever student Health Data Fest with SPH, transforming environmental datasets into actionable strategies for tackling the growing threat of toxic cyanobacteria blooms,
- Hosted expert guest speakers, including Yann LeCun and Celia Merzbacher,
- Launched our External Advisory Committee of industry experts who will help bridge the gap between the university and the technological landscape...
- ...And in collaboration with ARIA, established a new AI Commons for the University in the Barus Building.

DSI is welcoming two new excellent additions to our faculty, starting today! Join us in welcoming Dr. Larry Han, Assista...
07/01/2026

DSI is welcoming two new excellent additions to our faculty, starting today! Join us in welcoming Dr. Larry Han, Assistant Professor of Data Science and Biostatistics, and Dr. Ben Savitzky, Assistant Professor of the Practice for Math/Deep Learning.

Dr. Han comes to us from Northeastern University, where he served as an Assistant Professor of Biostatistics, alongside an appointment as an Affiliate Investigator at the Fred Hutch Cancer Center. Dr. Han’s research centers on creating innovative statistical and machine learning methods to utilize real-world data to improve public health and clinical medicine. His work specifically focuses on developing robust and targeted estimators for learning causal effects from large-scale observational studies and randomized trials, with broader interests spanning federated learning, data integration, and survival analysis. Dr. Han earned his PhD and AM in Biostatistics from Harvard University, followed by a postdoctoral fellowship in Health Care Policy at Harvard Medical School. A highly decorated scholar, his academic background also includes an MPhil from the University of Cambridge as a Gates Cambridge Scholar, an MA from Tsinghua University as a Schwarzman Scholar, and a BS from UNC-Chapel Hill as a Morehead-Cain Scholar.

Dr. Savitzky earned his M.S. and Ph.D. in Physics from Cornell University. Most recently, he has served as a Principal Investigator and Senior Scientist at h-Bar Instruments, following several years as a postdoctoral scientist at the Lawrence Berkeley National Laboratory's National Center for Electron Microscopy. Dr. Savitzky’s research bridges the physical sciences and data science, focusing on experimental methods, reconstruction algorithms, and open-source software tools for scanning transmission electron microscopy (STEM). His professional career also reflects a strong dedication to education, spanning early-career experience as a high school mathematics and physics teacher to university-level instruction as a teaching assistant and research mentor.

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