I have held both industry and academic research roles, and so my research interests are quite varied.
Whilst in industry, my research focused on the application of signal processing and machine learning tools for real-time management of power networks. In particular, I have been interested in designing tools that would allow network operators in the UK to effectively prepare for widespread adoption of electric vehicles and the associated increase in charging infrastructure.
Immediately prior to this, my academic research was primarily focused on the study of spatial point patterns and the stochastic processes that we can use to model these patterns. In particular, I am interested in the second-order properties of these patterns: given an observed point pattern, how can we accurately describe the interaction of points with one another, and can we build point process models that accurately replicate this behaviour in simulated data?
I also maintain an interest in both Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methodology. My previous work has covered both theoretical and methodological aspects of likelihood-free Monte Carlo methods.