Research Interests

I work on Bayesian and frequentist statistical modelling, machine learning and data science.

Most of my research centres on computational tools for this purpose, for example

• sequential Monte Carlo methods (a.k.a. "particle filters"),
• Markov chain Monte Carlo methods,
• variational inference.

My work aims to extend and combine these methods in novel ways to make them more amenable to the complex (e.g. high-dimensional) models nowadays often preferred by practitioners.

I am also keen on collaborating on real-world applications of such methods, for example in molecular biology, ecology, econometrics/finance, engineering and sports science.

PhD Students

• Jonah Drake