We are a diverse group of researchers spanning many interests across machine learning, computational statistics and statistical methodology. There are ten faculty members spread over three overlapping subgroups.
Faculty
![François Caron](/img/people/caron.jpg)
François Caron
Statistical Machine Learning, Bayesian methods, Bayesian nonparametrics, Statistical Network Analysis
![George Deligiannidis](/img/people/male.png)
George Deligiannidis
Computational Statistics, Monte Carlo methods
![Arnaud Doucet](/img/people/doucet.jpg)
Arnaud Doucet
Computational Statistics, Monte Carlo methods
![Robin Evans](/img/people/evans.jpg)
Robin Evans
Graphical models, causality, algebraic statistics
![Chris Holmes](/img/people/c-holmes_square.jpg)
Chris Holmes
Decision theory, biostatistics and precision medicine, probabilistic learning under model misspecification
![Geoff Nicholls](/img/people/nichollsPB.jpg)
Geoff Nicholls
Statistical modeling, Bayes Methods, Monte Carlo Methods.
![Tom Rainforth](/img/people/rainforth.jpeg)
Tom Rainforth
Machine learning, Bayesian inference, Probabilistic programming, Deep generative models
![Patrick Rebeschini](/img/people/rebeschini.jpg)
Patrick Rebeschini
Learning theory, Optimization, Implicit Regularization
![Judith Rousseau](/img/people/IMG_2305.jpg)
Judith Rousseau
Bayesian statistics, Asymptotics, Nonparametric statistics
![Dino Sejdinovic](/img/people/sejdinovic.jpg)
Dino Sejdinovic
Statistical machine learning, kernel methods, nonparametric statistics
![Yee Whye Teh](/img/people/teh.png)
Yee Whye Teh
Bayesian nonparametrics, probabilistic learning, deep learning
Affiliated Faculty
![Sarah Filippi](/img/people/filippi.jpg)
Sarah Filippi
Statistical machine learning and Bayesian statistics motivated by applications in biomedicine
Post-docs
![M. Azim Ansari](/img/people/male.png)
M. Azim Ansari
Statistical Genetics, Evolution, Host Pathogen Interactions, Computational Biostatistics, Machine Learning, Bayesian Statistics
![Emile Mathieu](/img/people/mathieu.jpg)
Emile Mathieu
Probabilistic inference, Deep learning, Generative models, Representation Learning, Geometry
![George Nicholson](/img/people/nicholson.jpg)
George Nicholson
Computational biostatistics, machine learning, precision medicine
Graduate Students
![Moustafa Abdalla](/img/people/abdalla.jpg)
Moustafa Abdalla
Multi-view Learning, Time-series modelling, Statistical Genetics, Drug Development, High-throughput screening
![Freddie Bickford Smith](/img/people/bickfordsmith.jpeg)
Freddie Bickford Smith
Deep Learning, Uncertainty Estimation
![Shahine Bouabid](/img/people/bouabid.jpg)
Shahine Bouabid
Kernel Methods, Gaussian processes, Climate emulation
![Christian Carmona Perez](/img/people/chris_carmona.jpg)
Christian Carmona Perez
Methods for Bayesian modeling under mispecification
![Anthony Caterini](/img/people/caterini.jpg)
Anthony Caterini
High-Dimensional Statistics, Monte Carlo Methods, Variational Inference
![Sam Davenport](/img/people/davenport.png)
Sam Davenport
Gaussian Processes, fMRI data, Resampling methods, Random Field Theory
![Emilien Dupont](/img/people/dupont.png)
Emilien Dupont
Deep Learning, Generative Models
![Fabian Falck](/img/people/falck.jpg)
Fabian Falck
Probabilistic Deep Learning, Deep Generative Models, Causality, Applications in Health
![Tyler Farghly](/img/people/farghly.jpg)
Tyler Farghly
Learning theory, Optimisation, Monte Carlo methods
![Jake Fawkes](/img/people/fawkes.jpg)
Jake Fawkes
Causal Inference, Machine Learning, Fairness
![Edwin Fong](/img/people/fong.png)
Edwin Fong
Bayesian inference under model misspecification, Bayesian nonparametrics
![Adam Foster](/img/people/foster.jpg)
Adam Foster
Probabilistic machine learning, deep learning, unsupervised representation learning, optimal experimental design, probabilistic programming
![Adam Goliński](/img/people/golinski.jpg)
Adam Goliński
Probabilistic Inference, Probablistic Programming
![Aidan N. Gomez](/img/people/gomez.jpg)
Aidan N. Gomez
Neural networks and deep learning
![Frauke Harms](/img/people/harms.jpg)
Frauke Harms
combinatorics, computational complexity, Bayesian nonparametrics, machine learning, stochastic geometry
![Bobby He](/img/people/he.jpg)
Bobby He
Machine learning, deep learning, uncertainty quantification
![Zhiyuan Hu](/img/people/hu.jpg)
Zhiyuan Hu
Single-Cell Analysis, Ovarian Cancer, Genomics
![Robert Hu](/img/people/rhu.jpg)
Robert Hu
Machine Learning, Kernel Methods, Causal Inference
![Desi R. Ivanova](/img/people/ivanova.jpg)
Desi R. Ivanova
Bayesian Inference, Statistical Machine Learning, Optimal Experimental Design
![Jannik Kossen](/img/people/kossen.jpg)
Jannik Kossen
Active Learning, Bayesian Deep Learning, Transformers
![Charline Le Lan](/img/people/lelan.jpg)
Charline Le Lan
Probabilistic Inference, Deep Learning, Reinforcement Learning
![Cong Lu](/img/people/lu_c.jpeg)
Cong Lu
Deep Reinforcement Learning, Meta-Learning, Bayesian Optimisation
![Ning Miao](/img/people/miao.jpg)
Ning Miao
Deep generative models
![Cian Naik](/img/people/naik.jpg)
Cian Naik
Bayesian nonparametrics, Statistical Network Analysis
![Francesca Panero](/img/people/panero.jpg)
Francesca Panero
Bayesian random graphs, Bayesian nonparametrics, disclosure risk
![Emilia Pompe](/img/people/pompe.png)
Emilia Pompe
MCMC methods, Bayesian statistics
![Tim Reichelt](/img/people/reichelt.jpg)
Tim Reichelt
Probabilistic Programming, Probabilistic Inference
![Tim G. J. Rudner](/img/people/rudner.jpg)
Tim G. J. Rudner
Probabilistic inference, reinforcement learning, Gaussian Processes
![Yuyang Shi](/img/people/shi.jpg)
Yuyang Shi
Statistical Machine Learning, Deep Learning, Generative Models
![Jean-Francois Ton](/img/people/ton-photo_1.jpeg)
Jean-Francois Ton
Kernel methods, Meta-learning
![Hanwen Xing](/img/people/male.png)
Hanwen Xing
Computational methods, Bayesian inference
![Jin Xu](/img/people/xu.jpg)
Jin Xu
Meta-learning, equivariance in deep learning
![Schyan Zafar](/img/people/schyanzafar_bw.jpg)
Schyan Zafar
Monte Carlo methods, Multivariate stochastic processes
![Sheheryar Zaidi](/img/people/zaidi.jpg)
Sheheryar Zaidi
Statistical Machine Learning, Deep Learning
Former Members
- Louis Aslett
- Fadhel Ayed
- Remi Bardenet
- Marco Battiston
- Benjamin Bloem-Reddy
- Levi Boyles
- Ryan Christ
- Giuseppe Di Benedetto
- Lloyd Elliott
- Seth Flaxman
- Bradley Gram-Hansen
- Leonard Hasenclever
- Pierre Jacob
- Yunlong Jiao
- Hyunjik Kim
- Adam R. Kosiorek
- Ho Chung Leon Law
- Juho Lee
- Zhu Li
- Thibaut Lienart
- Xiaoyu Lu
- Simon Lyddon
- Chris J. Maddison
- Kaspar Märtens
- Xenia Miscouridou
- Jovana Mitrovic
- Konstantina Palla
- Valerio Perrone
- Dominic Richards
- David Rindt
- Jennifer Rogers
- Andrew Roth
- Patrick Rubin-Delanchy
- Tammo Rukat
- Sebastian Schmon
- Joost van Amersfoort
- Stefan Webb
- Matthew Willetts
- Chieh-Hsi (Jessie) Wu
- Qinyi Zhang
- Yuan Zhou