About me
I am a tenure-track assistant professor in the Department of Statistics at the University of California, Riverside. I am also a faculty member of the UCR Graduate Program in Genetics, Genomics & Bioinformatics (GGB). Previously, I was a postdoctoral fellow at the University of Texas MD Anderson Cancer Center from 2022 to 2024. I received my Ph.D. in Statistics from North Carolina State University in 2022.
My research lies at the intersection of statistical machine learning, computational statistics, and numerical optimization, with applications in artificial intelligence, bioinformatics, and cancer biology. My current methodological work focuses on: (1) principled evaluation of large language models, and (2) transfer learning across heterogeneous datasets. I also collaborate on cancer biology and genomics projects, including MYC acetylation in breast cancer and germline TP53 variation in Li-Fraumeni syndrome.
I am actively looking for highly motivated Ph.D. students from Statistics and GGB. Interested students are welcome to email me their CV and a brief description of their research interests.
News
- June 2026: Honored to receive the UCR RED Small Grant Award!
- June 2026: Congratulations to Xinhao on receiving the Florence Nightingale David Award for Insightful Statistical Application at the Florence Nightingale David Research Symposium!
- June 2026: Congratulations to Xinhao on receiving the Morris J. Garber Award!
- June 2026: Honored to receive the Rho Sigma Rao Faculty Award!
- May 2026: Our paper, An Interpretable and Scalable Framework for Evaluating Large Language Models, is now available on arXiv!
- April 2026: Our paper, Transfer Learning for Robust Structured Regression with Bi-level Source Detection, is now available on arXiv!