I am a second-year DPhil candidate in the Machine Learning Research Group at the University of Oxford, and a member of the Autonomous Intelligent Machines and Systems Centre for Doctoral Training (AIMS CDT).

My broad research interest is in inductive biases, particularly in geometric deep learning and graph neural networks. I’m also interested in reinforcement learning, dynamics, ML for finance, and probabilistic methods, including Bayesian deep learning, Gaussian processes, variational inference and probabilistic numerics (Bayesian optimisation/quadrature).

I previously worked on the HumBug project, which uses deep learning to detect and identify mosquito species by their flight tone using budget smartphones. I completed my MEng in Engineering Science, specialising in information engineering, at the University of Oxford, and was supervised by Prof. Michael Osborne in my fourth-year project.

In my spare time I enjoy reading, playing D&D, and exploring new pubs, especially those with real ale. I maintain a table of ratings and useful information about every pub in Oxford here.

News

06/08/2023: DRew covered in round-up blog post by @michael_galkin: Graph Machine Learning @ ICML 2023

28/07/2023: DRew discussed in keynote talk by @mmbronstein at TAG-ML workshop at ICML 2023.

19/06/2023: Presented DRew to Learning on Graphs and Geometry (LoGG) reading group (recording here). Blog post based on DRew published on Towards Data Science.

23/04/2023: First-author paper, “DRew: Dynamically Rewired Message Passing with Delay”, accepted at ICML 2023.