About me

I am a fifth-year PhD student in Statistics at UC Berkeley, where I work on theoretical machine learning and statistics with Song Mei and Peter Bartlett. Before Berkeley, I received a B.S. in Statistics from Peking University, where I work with Cheng Zhang.

My work focuses on understanding the statistical foundations of AI and on developing theory-inspired algorithms for AI. I use and extend tools from statistical learning theory, high-dimensional statistics, and optimization to study, e.g., the foundations of multimodal generative AI, scaling laws, Transformers, in-context learning, and to build mathematically motivated algorithms for AI alignment.

I am also broadly interested in LLM reasoning, high-dimensional statistics, and statistical inference. In my spare time, I enjoy basketball, hiking and traveling.