About Me

Welcome to my homepage! I am a second-year Ph.D. student in Statistics at the University of Toronto, advised by Professor Radu Craiu and Professor Monica Alexander. I am also an Affiliate Researcher at the Vector Institute and supported by the Data Sciences Institute (DSI) Doctoral Student Fellowship.

My research focuses on Bayesian methodology, deep generative modeling, and probabilistic inference for complex data. I am also thinking about how deep generative models can empower scalable Bayesian computation. I co-organize the department’s Bayesian reading group. If you’d like to collaborate, chat about research/life, or give a guest talk at our reading group, please feel free to drop me an email!

Back in the day, I received my M.S. in Statistics from the University of Chicago in 2024, where I spent two wonderful and intellectually stimulating years, and was fortunate to be mentored by Professor Dacheng Xiu and Professor Per Mykland. My master’s thesis was on large-scale realized volatility prediction with machine learning (see my presentation slides). Before UChicago, I received my B.S. in Statistics and Financial Mathematics also from UofT.

Influenced by my prior academic training and research, I have continued to develop a side interest in financial machine learning. Outside of research, I spend a decent amount of time behind the lens and on the court. I enjoy the theory and practice of photography, and I carry the spirit of sportsmanship in the game of basketball and life.