I am now a Postdoctoral Fellow in the Department of Statistics at Harvard University, under the supervision of Prof. Zheng (Tracy) Ke. I obtained my Ph.D. degree in Statistics at UC Davis, where I was fortunate to be co-advised by Prof. Krishna Balasubramanian and Prof. Wolfgang Polonik. Before coming to UC Davis, I received my Bachelor’s degree in Math at Fudan University, where I was advised by Prof. Lei Shi.

I am broadly interested in statistical problems arising in machine learning, deep learning and other applications. I am working on topics including:

• Geometric and topological statistics including graph-based statistics and topological data analysis (TDA).
• Network analysis
• Statistical learning including nonparametric statistics, kernel method and deep learning theories.

Recent News

• I will give a talk titled `On the nonasymptotic statistical inferences via stabilization theory of Gaussian approximation bounds’ at the 22nd INFORMS Applied Probability Society Conference at Georgia Institute of Technology from June 30th to July 3rd, 2025.
• Our recent work Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators is now avaible on Arxiv! Taking ATE as an example, we provide a general framework for non-asymptotic statistical inference via a local geometric concept called `stabilization’.
• I joined the Department of Statistics, Harvard University, on September 1, 2024, as a Postdoctoral Fellow.