I am currently an assistant professor at the Department of Statistics and Actuarial Science at the University of Hong Kong.

I was previously a data scientist at Novo Nordisk, where I developed novel statistical methods within the healthcare setting. Before that, I completed my PhD at the University of Oxford and the Alan Turing Institute, supervised by Prof. Chris Holmes.

Research

My current research explores Bayesian methods that are motivated by prediction - this encompasses topics in Bayesian nonparametrics, scalable inference, and model selection. In particular, I find generalized Bayesian procedures to be an exciting avenue of research for tackling issues like scalability and model misspecification. Some examples of these methods include general Bayesian updating, the Bayesian bootstrap and the martingale posterior.

My work also touches on topics in machine learning and conformal prediction. I’ve also recently started to take an interest in causal inference and its applications in clinical trials, as well as the overlap with Bayesian techniques.

Prospective postdocs/students

Update: I’m looking for a motivated postdoctoral fellow with a strong background in Bayesian nonparametric methods to join my group at HKU. If you are interested in working with me, please drop me an email with your CV and research interests. Unfortunately, due to the large volume of emails I receive, I may not be able to respond to each one individually.

I will unfortunately not be recruiting PhD students for the coming 2025/2026 academic year.

News

• I am honoured to have received the Savage Award for my PhD thesis on the predictive view of Bayesian inference.
• I presented our JRSSB discussion paper on martingale posterior distributions at the Royal Statistical Society in December 2022.
• My work on the marginal likelihood and cross-validation was featured on Talking Machines, Ferenc Huszár’s blog, and Christian Robert’s blog.