Our students

Compass students are passionate about their research interests and the impact they can make in the world through their work.

Take a look at our student-penned blog series Student perspectives to learn more about our students’ research and experiences on the Compass programme.  Also see our Alumni page for details of their final thesis and their first career destinations.


Cohort 1 (2019/20 start)​

Alessio Zakaria

Project title: Online Methods for Complex Stochastic Optimization Problems

Supervisors: Vladislav Tadic, Christophe Andrieu

  Daniel Williams

Project title: Estimating Probabilistic Models on Curved Surfaces using Score Matching

Supervisor: Song Liu

Doug Corbin

Project title: Non-parametric supervised learning. In particular, Doug’s work focusses on the application of nonparametric methods to sequential decision making problems.

Supervisors: Anthony Lee, Mathieu Gerber

Mauro Camara Escudero

Project title: Using Variational approaches to perform computationally efficient ‘divide and conquer’ Monte Carlo inference on demographic models.

Supervisors: Christophe Andrieu, Mark Beaumont (School of Biological Sciences).

Cohort 2 (2020/21 start)

Annie Gray

Project title: Exploratory data analysis of graph embeddings: exploiting manifold structure

Supervisors: Patrick Rubin-Delanchy and Nick Whiteley

Anthony Stephenson

Project title: Fast Bayesian Inference at Extreme Scale

Supervisors: Robert Allison and IBM

Conor Crilly

Project title: Uncertainty Quantification for Computer Experiments

Supervisors: Oliver Johnson and AWE

Conor Newton

Project title: Decentralised sequential decision making and learning

Supervisors: Henry Reeve, Ayalvadi Ganesh

Dan Ward

Project title: Simulation-Based Inference for Agent-Based Models

Supervisors: Matteo Fasiolo, Mark Beaumont (School of Biological Sciences)

Ed Davis

Project title: Graph embedding: time and space

Supervisors: Dan Lawson, Patrick Rubin-Delanchy

Euan Enticott

Project title: Scalable Additive Models for Forecasting Electricity Demand and Renewable Production

Supervisors: Matteo Fasiolo, Nick Whiteley, and EDF

  Jack Simons

Project title: Approximate Bayesian Inference by Density Ratio Estimation

Supervisors: Song Liu, Mark Beaumont (School of Biological Sciences)

Sam Stockman

Project title: Machine Learning and Point Processes for Insights into Earthquakes and Volcanoes

Supervisors: Maximillian Werner (School of Earth Sciences), Dan Lawson

Shannon Williams

Project title: The statistical design of assessments of impacts from explosive volcanic eruptions

Supervisors: Jeremy Phillips (School of Earth Sciences), Anthony Lee


Cohort 3 (2021/22 start)

Ben Griffiths

Project title: Developing scalable fitting methods for quantile and loss-based GAMs

Supervisors: Matteo Fasiolo and EDF

Daniel Milner

Project title: A spatially explicit assessment of agro-pastoral sustainability in Kenya and Ethiopia

Supervisors: Andrew Dowsey, Levi Wolf

Dominic Broadbent

Project title: Data reduction and large-scale inference

Supervisors: Nick Whiteley, Robert Allison, and NCSC

Edward Milsom

Project title: Classification for deep kernel machines

Supervisor: Laurence Aitchison

Emerald Dilworth

Project title: Using web data to detect spatial relationships

Supervisors: Emmanouil Tranos, Dan Lawson

Ettore Fincato

Project title: Functional Analysis of the Gibbs Sampler

Supervisors: Christophe Andrieu, Mathieu Gerber

Hannah Sansford

Project title: Graph simulation

Supervisors: Nick Whitely, Patrick Rubin-Delanchy

Harry Tata

Project title: Novel semi-supervised Bayesian learning to rapidly screen new oligonucleotide drugs for impurities

Supervisors: Andrew Dowsey and AstraZeneca

Josh Givens

Project title: (Differential) Model Inference with Imperfect Information

Supervisors: Song Liu, Henry Reeve

Tennessee Hickling

Project title: Flexible tails for normalising flows

Supervisor: Dennis Prangle

Cohort 4 (2022/23 start)

Ben Anson

Project title: Graph deep kernel machines

Supervisor: Laurence Aitchison (Department of Computer Science)

Codie Wood

Project title: Misclassification in binary and categorical variables: development of methods and software for epidemiology

Supervisors: Kate Tilling & Rachael Hughes from Bristol Medical School (Population Health Science), Jonathan Bartlett (London School Hygiene Tropical Medicine)

Dylan Djik

Project title: Robust estimation and inference for high-dimensional time series

Supervisor: Haeran Cho

Emma Ceccherini

Project title: Covariate Information for Dynamic Network Embedding

Supervisors: Ian Gallagher, Dan Lawson

Emma Tarmey

Project title: Variable selection in causal inference: development of methods and software for epidemiology

Supervisors: Kate Tilling & Jonathan Sterne from Bristol Medical School (Population Health Science), Rhian Daniel (Cardiff University)

Henry Bourne

Project title: Investigating the Effect of Latent Representations on Continual Learning Performance

Supervisor: Rihuan Ke

Qi Chen

Project title: Methodology for inferring directed graphs representing generative processes

Supervisor: Dan Lawson

 Rachel Wood

Project title: Comparing qualitatively different data at scale

Supervisor: Dan Lawson

Rahil Morjaria

 Project title: New Directions in Group Testing

Supervisor: Sid Jaggi

Sam Bowyer

 Project title: Fast and correct Bayesian inference with massively parallel methods

 Supervisor: Laurence Aitchison (Department of Computer Science)

 Samuel Perren

Project title: Validity of population adjustment methods for disconnected networks of evidence

Supervisors: Nicky Welton, David Phillippo & Hugo Pedder from Bristol Medical School (Population Health Science)

Xinrui Shi

 Project title: Network Meta-Analysis

 Supervisor:  Ayalvadi Ganesh


Cohort 5 (2023/24 start)



Cecina Babich Morrow

Mini project: Sensitivity of Bayesian Decision Analysis: a tool for robust climate adaptation decision making

Supervisors: Dennis Prangle, Dan Bernie, Laura Dawkins (MetOffice)


Oliver Baker

Mini project: Entropy of Soft Random Geometric Graphs

Supervisor: Carl Dettman


Daniel Gardner

Mini project: Boolean Modelling for Genetic Pathway Modelling

Supervisors: Mark Beaumont, Feng Yu


Xinyue Guan

Mini project: Dynamic covariance matrix models for energy forecasting

Supervisors: Matteo Fasiolo, Haeran Cho


Vera Hudak

Mini project: Network meta-analysis of diagnostic test accuracy

Supervisors: Nicky Welton,Hayley Jones


Sherman Khoo

Mini project: Simulator-based statistical inference with score matching

Supervisors: Song Liu, Mark Beaumont


Daniella Montgomery

Mini project: Haplotype-Based Methods for the Efficient Detection of Problematic Recombinogenic Pathogen Lineages at Scale

Supervisor: Dan Lawson


Kieran Morris

Mini project: Hirschfeld–Gebelein–Rényi maximum correlation

Supervisors: Oliver Johnson, Sid Jaggi


Grace Yan

Mini project: Scaling up simulation based inference to whole genome data

Supervisors: Dennis Prangle, Mark Beaumont



Yuqi Zhang

Mini project: Change Point Detection on Factor Models

Supervisor: Haeran Cho


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