I am a postdoc at the Wharton Department of Statistics and Data Science, advised by Yuejie Chi and Yuxin Chen. 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

  • 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 papers
Preprint

Sample efficient inductive matrix completion with noise and inexact side information.

Yuepeng Yang, Cong Ma

arXiv, 2026

arXiv
Preprint

Estimating shared subspace with AJIVE: the power and limitation of multiple data matrices.

Yuepeng Yang, Cong Ma

arXiv, 2025

arXiv
JASA

Random pairing MLE for estimation of item parameters in Rasch model.

Yuepeng Yang, Cong Ma

Journal of the American Statistical Association, 2026

arXiv JASA
COLT

Top-K ranking with monotone adversary.

Yuepeng Yang, Antares Chen, Lorenzo Orecchia, Cong Ma

Conference on Learning Theory, 2024

arXiv COLT Slides