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 research studies the statistical foundations of learning from heterogeneously structured data. Recent projects include low-rank matrix estimation with multi-view integration, ranking from pairwise comparisons beyond uniform sampling, and robust reinforcement learning.

News

  • Oct 2026 New preprint on ranking from pairwise comparisons on general comparison graphs. We establish entrywise error bounds for MLE and Rank Centrality that is captured by algebraic connectivity of the comparison graph. We then show that both algorithms are robust against outcome-adaptive data augmentation.

Selected Papers

All papers
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 a monotone adversary.

Yuepeng Yang, Antares Chen, Lorenzo Orecchia, Cong Ma

Conference on Learning Theory, 2024

arXiv COLT Slides
Preprint

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

Yuepeng Yang, Cong Ma

arXiv preprint, 2025; minor revision at JMLR

arXiv Slides

Recent Papers

All papers
Preprint

Graph-monotone entrywise guarantees for MLE and Rank Centrality on general comparison graphs.

Yuepeng Yang, Cong Ma

arXiv, 2026

arXiv
Preprint

Bias-corrected subspace intersection: minimax-optimal shared subspace estimation in multi-view data.

Xianwen Song, Yuepeng Yang, Cong Ma

arXiv, 2026

arXiv
Preprint

Robust average-reward Markov decision processes: minimax-optimal learning via plug-in reductions.

Yuepeng Yang, Yuxin Chen, Yuejie Chi

arXiv, 2026

arXiv Poster
Preprint

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

Yuepeng Yang, Cong Ma

arXiv, 2026

arXiv