Data Science Institute

Yu Cheng is an Assistant Professor in the Department of Computer Science at Brown University. His main research interests include machine learning, optimization, and game theory. Recently his work focuses on the design and analysis of scalable and provably robust algorithms for machine learning.

Yu received his Ph.D. in Computer Science from the University of Southern California in 2017, advised by Shang-Hua Teng. Before joining Brown University in 2022, Yu was a postdoc at Duke University, a visiting member at the Institute for Advanced Study, and an Assistant Professor at the University of Illinois at Chicago.

How does your research, teaching, or other work relate to data or computational science?

My main research interests include machine learning, optimization, and game theory. My recent work focuses on the design and analysis of scalable and provably robust algorithms for machine learning, especially in the areas of high-dimensional robust statistics, non-convex optimization, and learning with strategic agents.