I am a Senior Lecturer in Machine Learning at the School of Informatics of the University of Edinburgh, affiliated with the Institute for Adaptive & Neural Computation.

I am broadly interested in developing methods for inference and experimental design and applying them to significant problems in the natural sciences.

Recent papers:

• New on arXiv: Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds

• Accepted to ICLR 2021: Neural Approximate Sufficient Statistics for Implicit Models (Spotlight)

• Accepted to NeuRIPS 2020: Telescoping Density-Ratio Estimation (Spotlight, top 4% of submissions)

• Appearing in Bayesian Analysis: Likelihood-Free Inference by Ratio Estimation

• New paper in Bayesian Analysis: Sequential Bayesian Experimental Design for Implicit Models via Mutual Information