I’m an associate professor in statistics at the University of Bristol.
My current research is on the interface between Bayesian statistics and machine learning. I am particularly interested in developing approximate inference methods such as simulation based inference approaches, variational inference and composite likelihood. One application is to likelihood-free inference, where simulation of data is possible but the likelihood function is unavailable. Another is to stochastic differential equations I’ve worked on applications to population genetics, physics, ecology and epidemiology. I’m also interested in experimental design and how to quickly derive effective high dimensional designs.