Compass Alumni

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 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 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 Jack Simons
Research Scientist, InstaDeep

Thesis: Simulation-based Inference using contemporary 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 Research Associate, University of Bristol

Thesis: Enhancing Earthquake Forecasting: Machine Learning Applications in Point Process Models – supervised by Maximillian Werner and Dan Lawson

 

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