Hi! I am a postdoctoral researcher with Toniann Pitassi and Richard Zemel at Columbia University, and also part of Simons Collaboration on the Theory of Algorithmic Fairness. Previously, I completed my Ph.D. in the Theory of Computation group at Harvard University, advised by Cynthia Dwork. I am also fortunate to work with David Parkes, Weijie Su, and James Zou on various projects.
My research interests lie at the intersection of theoretical computer science and responsible machine learning. In particular, I develop formal frameworks to address algorithmic and societal challenges in modern data science such as risk control of foundation models, fairness, and privacy. My tools mainly draw on distribution-free uncertainty quantification, (multi-)calibration, and reinforcement learning.