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: Variational Gibbs Inference for Statistical Model Estimation from Incomplete Data

• NeuRIPS 2021 paper: Implicit Deep Adaptive Design: Policy–Based Experimental Design without Likelihoods

• NeuRIPS 2021 AI for Science Workshop paper: Bayesian Optimal Experimental Design for Simulator Models of Cognition

• 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)