About

I am currently a Ph.D. candidate in Biostatistics at the University of California, Los Angeles (UCLA), where I also earned my M.S. in Biostatistics. Prior to that, I received a B.B.A. in Financial Services with a minor in Applied Mathematics from The Hong Kong Polytechnic University.

My research interests include causal inference, survival analysis, high-dimensional data analysis, and statistical machine learning. At UCLA, under the mentorship of Dr. Gang Li, my work focuses on developing methodologies for complex time-to-event data. This includes novel instrumental variable approaches and predictive model evaluation in the presence of competing risks. I have worked on topics such as synthetic IV estimation for censored restricted mean survival time (RMST), interpretable machine learning for clinical risk prediction, and epidemic modeling.

Beyond research, I serve as a teaching assistant for graduate-level courses including Mathematical Statistics, Linear Models, Multivariate Biostatistics, and Survival Analysis. I’ve also contributed to the Summer Institute in Statistics and Modeling of Infectious Diseases (SISMID) at Emory University as a teaching assistant. Additionally, I work as a statistician in the UCLA School of Medicine’s COPD Program, where I collaborate with medical professionals to design analyses, interpret complex data, and effectively communicate results.

Outside of academics, I enjoy playing tennis, badminton, and table tennis.