About me

I am a Ph.D. student in Statistics at the University of Chicago, co-advised by Professor Cong Ma and Professor Chao Gao. Prior to joining UChicago, I received my undergraduate degree in Mathematics from School of the Gifted Young at University of Science and Technology of China.

Research Interests

My research lies broadly at the intersection of statistical machine learning and information theory. I am particularly interested in understanding the fundamental limits of statistical estimation and inference in the non-asymptotic regime, as well as developing methods that are theoretically optimal and practically reliable under minimal assumptions. Detailed topics include:

• Robust statistics: structured contamination mechnisms and smoothed adversaries beyond Huber’s formulation; adaptive procedures for robust estimation and robust uncertainty quantification; interaction between robustness, sparsity, and dependence.
• Ranking from pairwise comparisons: graph-specific optimality results; models beyond Bradley–Terry–Luce.
• Adaptation and instance-optimality: shape-agnostic location estimation, confidence intervals, and regression adapted to the instance-optimal rates.