I am a third year StatML student in the Department of Statistics at the University of Oxford.

My research interests include generative models, variational inference and MCMC. Recently, I have worked on denoising generative models for discrete data, viewing the process in continuous time and simulating with chemical physics inspired integrators. Previously, I have worked on online variational inference for sequential state space models by using links with reinforcement learning. I have also explored the links between variational inference and MCMC methods for more efficient sampling with applications to sampling molecular configurations from the Boltzmann distribution.