Compass Alumni – Compass Blog

Some of our Compass graduates are now pursuing careers in industry, or have taken up academic positions. You can find out more about them below.

	Dr Alessio Zakaria Mathematical Consultant, Smith Institute Thesis: Asymptotic Analysis of an Adaptive Stochastic Gradient Descent Non-convexity and Markovian Dynamics – supervised by Vladislav Tadic and Christophe Andrieu
	Dr Alexander Modell Research Associate in Statistics and Machine Learning, Imperial College London Thesis: Spectral embedding of large graphs and dynamic networks – supervised by Patrick Rubin-Delanchy
	Dr Annie Gray Researcher, The Alan Turing Institute Thesis: Statistical Exploration of the Manifold Hypothesis – supervised by Patrick Rubin-Delanchy and Nick Whiteley
	Dr Anthony Stephenson Senior Research Associate, Lancaster University Thesis: Fast Gaussian Process Regression at Extreme Scale – supervised by Robert Allison and IBM
	Dr Conor Crilly Research Data Scientist, University of Exeter Thesis: Uncertainty Quantification for Computer Experiments – supervised by Oliver Johnson
	Dr Dan Ward Postdoctoral Researcher, University of Bristol Thesis: Neural Methods for Practical Scientific Bayesian Inference – supervised by Matteo Fasiolo and Mark Beaumont
	Dr Danny Williams Machine Learning Engineer, Weaviate AI Thesis: Using Score-based Methods for Unnormalisable Probability Density Estimation: Truncated Density Estimation and Parameter Derivative Estimation – supervised by Song Liu
	Dr Dominic Owens Quantitative Macro Strategist, Pharo Management Thesis: Data Segmentation and High Dimensional Time Series Analysis – supervised by Haeran Cho and CheckRisk
	Dr Ed Davis Applied Scientist, Amazon Thesis: Beyond Spectral Unfoldings for Dynamic Network Embeddings – supervised by Dan Lawson and Patrick Rubin-Delanchy
	Edward Milsom Lecturer in Artificial Intelligence, University of Bath Thesis: Learning and Optimisation of Representations in Deep Learning – supervised by Laurence Aitchison
	Ettore Fincato Researcher, Advanced Risk and Portfolio Management (ARPM) Thesis: A theory for model-based nonsmooth optimization – supervised by Christophe Andrieu and Mathieu Gerber
	Dr Euan Enticott Senior Modelling Specialist, National Energy System Operator Thesis: Structured Additive Stacking models with application in the energy domain – supervised by Matteo Fasiolo and Nick Whiteley
	Dr Jack Simons Research Scientist, InstaDeepThesis: Simulation-based Inference with Modern Generative Methods – supervised by Song Liu and Mark Beaumont
	Dr Jake Spiteri Quantitative Strategist, BNP Paribas Thesis: Nonparametric Density Estimation with Kernel Mean Embeddings – supervised by Anthony Lee and Mathieu Gerber
	Dr Mauro Camara Escudero Machine Learning Engineer, ExTrac Thesis: Approximate Manifold Sampling: Robust Bayesian Inference for Machine Learning – supervised by Christophe Andrieu and Mark Beaumont
	Dr Michael Whitehouse Research Associate, School of Public Health, Imperial College London Thesis: Fast and Consistent Inference in Compartmental Models (Introducing Poisson Approximate Likelihood Methods) – supervised by Nick Whiteley
	Dr Sam Stockman Senior Data Scientist, Department for Environment, Food and Rural Affairs Thesis: Enhancing Earthquake Forecasting: Machine Learning Applications in Point Process Models – supervised by Maximillian Werner and Dan Lawson
	Shannon Williams Data Analyst, Planning Inspectorate Thesis: The Statistical Design of Assessments of Ash Hazard Impacts from Explosive Volcanic Eruptions – supervised by Jeremy Phillips and Anthony Lee