Chen Cheng

I'm a sixth year PhD student in Statistics at Stanford University, jointly advised by Professor John Duchi and Andrea Montanari. I am fortunate to be a recipient of the William R. Hewlett Stanford Graduate Fellowship. Prior to that, I received my Bachelor's degree in Computational Mathematics from Peking University.

I will graduate at the summer of 2025, and is actively on the job market.

I'm broadly interested in mathematical theory and algorithms for high dimensional data and statistical models. Over the years, I have worked on high dimensional statistical theory (random matrix under low rank perturbation, infinite dimensional random matrix theory and high dimensional gradient flow), statistical theory on machine learning (label aggregation, model aggregation, optimality under distributional shift, etc.), reinforcement learning and (entropy regularization), deep learning (overparameterization and high dimensional limit), conformal inference and differential privacy. I'm generally excited about all problems with the blend of theoretical challenges and real world applications.

Here are my CV and research statement. My google scholar page is here.