I am a fourth-year PhD student in Computer Science at University of California, Berkeley, advised by Moritz Hardt and Michael I. Jordan. My current research examines the theoretical foundations of machine learning and algorithmic decision-making, with a focus on societal impact and human welfare. Other interests include microeconomics and high-dimensional statistics.
Previously, I graduated with a BSE in Operations Research and Financial Engineering from Princeton University, where I was fortunate to work with Barbara Engelhardt, Han Liu, and Amit Singer. I have also spent two wonderful summers interning at Microsoft Research: hosted by Urun Dogan and Katja Hofmann in the Reinforcement Learning Group at MSR Cambridge in 2016, and hosted by Christian Borgs, Jennifer Chayes, and Adam Tauman Kalai at MSR-NE in 2019.
News | Our manuscript Bandit Learning in Decentralized Matching Markets is on arXiv.