I am a 5th-year Ph.D. candidate in the Department of Statistics at the University of California, Santa Cruz, advised by Prof. Zehang (Richard) Li. My research focuses on the development and application of parametric and non-parametric Bayesian models, with an emphasis on Bayesian latent variable models for prevalence estimation and cause-of-death prediction under domain adaptation (Google Scholar).

Beyond academia, I have industry research experience in causal inference, reinforcement learning, and large language models (LLMs). During my Ph.D., I worked as a Data Scientist Intern at Tencent America and Microsoft Azure, contributing to projects in treatment effect estimation, online experimentation, and AI/ML infrastructure.

Prior to my Ph.D., I earned my M.S. in Statistics from the University of California, Davis, where I was advised by Prof. James Sharpnack. Before transitioning into research, I worked as a full-stack Software Development Engineer at ThoughtWorks, gaining hands-on experience in software engineering, system design, and large-scale data processing.