I am a Bayesian statistician, currently a Ph.D. candidate in statistics at Duke University under the supervision of Dr. Jason Xu. I develop efficient Markov Chain Monte Carlo algorithms for problems characterized by high-dimensional missing data with applications in epidemiology and medicine.
I taught STA101 Data Analysis and Statistical Inference in Summer 2021 and Summer 2022 and am also mentoring Jenny Huang (major in statistical science) and Min Chen (Masters in statistical science).
I am spending this summer at the National Institute of Allergy and Infectious Diseases, NIH, where I develop a Julia package for fitting semi-Markov multistate models to panel data via the MCEM algorithm.
When not designing new MCMC samplers, I enjoy playing tennis, model making and cooking. I am also a fan of Formula 1.