Research group
Ben Howson

Ben Howson is a final year PhD student in the StatML Centre for Doctoral Training programme at Imperial College London co-supervised by Ciara Pike-Burke.
His research focusses on bandit and reinforcement learning problems, with a particular emphasis on developing provably efficient algorithms for the delayed feedback, human feedback, and multi-agent settings.
Prior to joining the StatML CDT, Ben completed his Master’s in Statistics at the University of Warwick.
Guiomar Pescador Barros

Guiomar Pescador Barrios is a PhD student at the Department of Mathematics at Imperial College London and part of the StatML Centre for Doctoral Training, a joint program with the University of Oxford, where she is collaborating with Mark van der Wilk and his research group.
Her research focuses on continual learning, Bayesian inference, and neural architecture selection. Currently, she is developing efficient methods for online learning and dynamic architecture selection, enabling models to adapt more effectively to new data and task requirements.
Before joining Imperial, she completed an integrated Master’s degree in Mathematics at the University of Edinburgh.
James Odgers

James Odgers is a PhD student in the Department of Mathematics and the Department of Computing at Imperial, co-supervised by Ruth Misener.
James’ research focuses on adapting and developing probabilistic latent variable models, including Gaussian Process latent variable models (GPLVMs), to improve pharmaceutical manufacturing techniques.
Prior to starting his Phd, James completed an MSci in Physics at Imperial College London.
Junyang Wang

Junyang Wang is a researcher in Computational Statistics, with a focus on Bayesian methodology. His research interests include Bayesian Computation, Probabilistic Numerics, Variational Inference, Applications of Bayesian methodology in sustainability and public health. He is currently working with Dr Sarah Filippi on developing scalable Bayesian mixture models using variational inference on mixed data, motivated by application of clustering risk factor data in order to identify useful phenotypes. He is collaborating with NCD-RisC on the application aspects of this work
Prior to this, Junyang completed a PhD in Statistics at Newcastle University on Bayesian Probabilistic Numerical Methods for Ordinary and Partial Differential Equations under supervision of Prof Chris Oates. He then worked as a Postdoctoral Research Associate in the Department of Civil and Environmental Engineeringat Imperial College on an interdisciplinary project developing Bayesian statistical methodology for material flow analysis (MFA).
Michael Komodromos

Michael Komodromos is a PhD student at the Department of Mathematics at Imperial College London and part of the StatML Centre for Doctoral Training. He is co-supervised by Dr Marina Evangelou and Prof Eric Aboagye from the Department of Surgery and Cancer at Imperial College London.
His research is focused on variational Bayes, high-dimensional regression and variable selection methods with applications within cancer diagnosis and prognosis.
Prior to his PhD, he completed an MSc. in Statistics at Imperial College London and a BSc. in Statistics, Economics and Finance at University College London.
Theodore de Pomereu

Theodore de Pomereu is a PhD student in the Fröhlich Lab at the Francis Crick Institute and the Department of Mathematics at Imperial College London, where he is supervised by Fabian Fröhlich and Sarah Filippi.
His research focuses on the development and application of statistical machine learning methods to find mathematical models of complex biological systems, with a particular emphasis on intracellular signalling networks and synthetic signalling cascades.
Prior to joining the Crick, Theodore completed his Master’s in Applied Mathematics (Part III) at the University of Cambridge and his Master’s of Engineering in Mathematics and Data Science at CentraleSupélec, Paris-Saclay University in France.
Previous members of the research group
- Dr Jonathan Ish-Horowicz – PhD student who graduated in 2022
- Dr Nia Iurilli – PhD student who graduated in 2021
- Dr Arinbjorn Kolbeinsson – PhD student who graduated in 2021
- Dr Onur Teymur – Postdoctoral research associate between 2018 and 2020
- Dr Qinyi Zhang – PhD student who graduated in 2019