Experience
Education
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Fields I have published work in include Bayesian deep learning • deep learning • approximate Bayesian inference • Gaussian processes • Bayesian modelling • Bayesian non-parametrics • scalable MCMC • generative modelling.
With applications including AI safety • ML interpretability • reinforcement learning • active learning • natural language processing • computer vision • medical analysis.

Broadly speaking, my interests lie in the fields of linguistics, applied maths, and computer science. Most of my work is motivated by problems found at the intersections of these fields, with an arching theme of research being understanding empirically developed machine learning techniques.