I am currently a researcher at PROWLER.io, where I work towards developing systems which learn to accomplish a task through experience from interacting with the environment, with as little experience as possible. I aim to let the underlying principles of inference and learning guide my work, both from the point of view of developing practical methods from first principles, and from finding underlying principles in existing methods.
I am particularly interested in reinforcement learning methods which use explicit predictive models of the world to plan behaviour. This approach improves data efficiency, as knowledge about the world generalises strongly to new situations. Learning good models of the world, with a reliable estimate of their own uncertainty, is crucial to the success of these methods.
A major component of my research is building better predictive models. In reinforcement learning / decision making applications, we require a) uncertainty estimates, for avoiding or taking calculated risks, and b) automatic adaptation with increasing data, as more experience is gained. Bayesian inference provides an elegant framework for representing uncertainty, and automating many aspects of the modelling process. Currently, I am interested in bringing the benefits of Bayesian inference to deep learning models, using Gaussian processes as a building block.
Before starting at Prowler, I obtained a PhD from the Machine Learning Group at the University of Cambridge, working with Carl Rasmussen, and completing my thesis in 2017. I was funded by the EPSRC and awarded a Qualcomm Innovation Fellowship for my final year. During my PhD, I occasionally worked as a machine learning consultant, and I also spent a few months in Mountain View, CA working on a Google ATAP project. I moved to the UK from the Netherlands for my undergraduate degree in Engineering, at Jesus College, University of Cambridge.
Machine Learning Researcher, 2017-present
PhD in Machine Learning, 2017
University of Cambridge, Machine Learning Group
MEng in Engineering, 2012
University of Cambridge