Data science, the study of obtaining value from data, is a fast‑emerging and distinctive field. It is driven by experts in several domains, computer scientists and statisticians who create and use increasingly sophisticated languages, tools, and methodologies that enable data‑driven decision making and problem solving. This diverse set of applications and tools, driven by domain‑oriented challenges of our increasingly data‑centric world, can often be translated and adapted for use in other fields, such as astronomy and astrophysics, economics, public policy, and cancer research.
In a way that is distinctive to the University of Chicago’s rigorous academic culture, researchers across the University not only develop new tools and techniques in their respective domains, they also consider the theoretical underpinnings of each new approach. This creates a natural ecosystem in which applications are developed across fields while simultaneously establishing a strong theoretical foundation for data science as a discipline, resulting in an accurate and theoretically sound basis for developing and translating existing and new applications.
Related Faculty
Founded in 2021, the Data Science Institute (DSI) executes the University of Chicago’s bold, innovative vision of Data Science as a new discipline. The DSI seeds research on the interdisciplinary frontiers of this emerging field, forms partnerships with industry, government, and social impact organizations, and supports holistic data science education.
The Data Science Institute partners with the UChicago Department of Computer Science and the UChicago Department of Statistics, and is co-located with UChicago CS in the John Crerar Library Building. But the scope of DSI stretches beyond these departments, facilitating research partnerships and programming for all UChicago divisions, departments, and schools. DSI is also part of an ambitious, multi-year expansion of computer and data science efforts at the University of Chicago.
Defining the Field of Data Science
Michael Franklin
- Liew Family Chairman of Computer Science
- Senior Advisor to the Provost for Computing and Data Science
- Faculty Co-Director, Data Science Institute
Michael J. Franklin is the inaugural holder of the Liew Family Chair of Computer Science. An authority on databases, data analytics, data management and distributed systems, he also serves as Senior Advisor to the Provost on Computation and Data Science and is Faculty Co-Director of the Data Science Institute.
Nick Feamster
- Neubauer Professor of Computer Science
- Faculty Director of Research, Data Science Institute
Nick Feamster is Neubauer Professor of Computer Science and Faculty Director of Research at the Data Science Institute. Feamster designs and deploys network protocols and systems that make the Internet work better, and uses empirical network measurement and machine learning to understand and improve network performance, security, and privacy
Rebecca Willett
- Professor, Departments of Computer Science and Statistics
- Faculty Director of AI, Data Science Institute
Rebecca Willett is a Professor of Statistics and Computer Science at the University of Chicago and Faculty Director of AI at the Data Science Institute. Her research interests include network and imaging science with applications in medical imaging, wireless sensor networks, astronomy, and social networks.
David Uminsky
- Senior Research Associate, Department of Computer Science
- Executive Director, Data Science Institute
David Uminsky joined the University of Chicago in September 2020 as a senior research associate and Executive Director of the Data Science Institute. He was previously an associate professor of Mathematics and Executive Director of the Data Institute at University of San Francisco (USF). His research interests are in machine learning, signal processing, pattern formation, and dynamical systems.
Aloni Cohen
- Assistant Professor, Computer Science and Data Science
Aloni Cohen is an Assistant Professor of Computer Science and Data Science at the University of Chicago. His research explores the interplay between theoretical cryptography, privacy, law, and policy. Specifically, he aims to understand and resolve the tensions between the theory of cryptography and the privacy and surveillance law that governs its eventual real-world context.
Chenhao Tan
- Assistant Professor, Computer Science and Data Science
Chenhao Tan is an assistant professor of computer science at the University of Colorado Boulder. His research interests include human-centered AI, natural language processing, and computational social science. His work has been covered by many news media outlets, such as the New York Times and the Washington Post.
