I work primarily on Reinforcement Learning and Design of Experiments, although I am broadly interested in Uncertainty in Machine Learning. Before graduate school I did some work on Probabilistic Modelling for transportation systems. See my Google Scholar for the most up to date list of academic publications.

Active Search

We argue that Deep RL is a particularly strong choice for active search tasks from decision-theoretic and computational perspectives.

OOD Detection

We challenge the recent view that test-time gradients offer unique advantages to OOD detection in deep networks.

Bayesian Modelling

We develop Bayesian models of traffic phenomena for use in real-time adaptive signal control systems.