I am a Bayesian statistician, currently a Ph.D. candidate in statistical science at Duke University advised by Dr. Jason Xu. I will defend in March 2024. I have developed efficient Markov chain Monte Carlo samplers for problems characterized by high-dimensional missing data with applications in contagious disease modeling, cancer natural history modeling and vaccines trials.
I taught STA101 Data Analysis and Statistical Inference in 2021 and 2022 at Duke University and have mentored Jenny Huang (major in statistical science) and Min Chen (Masters in statistical science).
I am currently interning at the National Institute of Allergy and Infectious Diseases, NIH, where I develop a Julia package that implements a Monte Carlo EM algorithm for fitting semi-Markov multistate models to panel data, with applications in vaccines trials.