Preprint
I am a postdoc at the Wharton Department of Statistics and Data Science, advised by Yuejie Chi and Yuxin Chen. Before joining Wharton, I was hosted at Yale University for a year. Previously, I completed my PhD in Statistics at the University of Chicago with Cong Ma. My work studies statistical and machine learning theory, with recent projects in matrix estimation, ranking, reinforcement learning, and multi-matrix data analysis.
News
- Aug 2026 Our new preprint develops minimax-optimal methods for robust average-reward Markov decision processes. Using plug-in reductions, we characterize how the sample complexity changes across high- and low-tolerance regimes.
- Jul 2026 I started as a postdoc at the Wharton Department of Statistics and Data Science.
- May 2026 Our new preprint asks how much imperfect side information can still help in inductive matrix completion. We show that low-rank matrices can be recovered sample-efficiently even when both the observations and the side information are noisy.
Recent Papers
All papersPreprint
Sample efficient inductive matrix completion with noise and inexact side information.
Preprint
Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices.
JASA