Eric Mazumdar is an Assistant Professor of Computing and Mathematical Sciences and Economics at the California Institute of Technology (Caltech), contributing to the Computer Science faculty. His research lies at the intersection of machine learning and economics. He is broadly interested in developing the tools and understanding necessary to confidently deploy machine learning algorithms into societal-scale systems. This work examines the theoretical underpinnings of learning algorithms in uncertain, dynamic environments where they interact with strategic agents, humans, and other algorithms. Practical applications span intelligent infrastructure, online markets, e-commerce, and healthcare delivery. Key topics include strategic classification, learning behavioral models of human decision-making from data, min-max optimization, learning in games, multi-agent reinforcement learning, distributionally robust learning, and learning for control. Mazumdar pursues principled approaches to algorithm design for strategic and dynamic environments, encompassing foundations for robust and resilient learning, scalable architectures and algorithms, and broader implications of algorithmic decision-making in society.

Mazumdar earned a B.S. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 2015 and a Ph.D. in Electrical Engineering and Computer Science from the University of California, Berkeley in 2021, co-advised by Michael I. Jordan and Shankar Sastry. He joined Caltech as Assistant Professor in 2021 and is affiliated with Control and Dynamical Systems as well as the FALCON/RSRG research groups. He received the NSF CAREER Award in 2023 for his proposal on Learning for Strategic Interactions in Societal-Scale Cyber-Physical Systems and a Research Fellowship for Learning in Games from the Simons Institute for Theoretical Computer Science. His research is supported by grants from NSF, DARPA, and Amazon. Mazumdar teaches courses including CDS 110 – Analysis and Design of Feedback Control Systems, CMS/CS/Ec/EE 144 – Networks: Structure & Economics, and CMS/Ec 248 – Topics in Learning and Games.

Professional Email: ericmazumdar@caltech.edu