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We do research in both theoretical machine learning, as well as applications of machine learning in various domains, including medical, astronomy, autonomous driving, and more.

Recent publications:
05/2021: "Think Global and Act Local: Bayesian Optimisation over High-Dimensional Categorical and Mixed Search Spaces" (Xingchen Wan, Vu Nguyen, Huong Ha, Binxin (Robin) Ru, Cong Lu, Michael A. Osborne).
05/2021: "PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning" (Angelos Filos, Clare Lyle, Yarin Gal, Sergey Levine, Natasha Jaques, Gregory Farquhar).
05/2021: "Active Testing: Sample-Efficient Model Evaluation" (Jannik Kossen, Sebastian Farquhar, Yarin Gal, Tom Rainforth).

Reproducibility and Code

One of our lab's missions is to contribute to the reproducibility effort. Here we provide code for our own research, as well as reproductions of works by others (e.g. ones we implemented as baselines as part of our own research).

Recent code release:
07/2020: OATomobile: A research framework for autonomous driving (Angelos Filos, Panagiotis Tigas).
07/2020: Slurm for Machine Learning (Joost van Amersfoort).
05/2020: Torch Memory-adaptive Algorithms (TOMA) (Andreas Kirsch).

Group Members

We are researchers coming from varied backgrounds, including Computer Science, Maths & Stats, Engineering, and Physics.

We come from academia (Oxford, Cambridge, MILA, Manchester, U of Amsterdam, U of Toronto, U of Cape Town, Yale, and others) and industry (Google, DeepMind, Twitter, Qualcomm, and startups).

We include 5 Rhodes Scholars, 3 Clarendon Scholars, 3 DeepMind Scholars, one cancer research UK Scholar, with our students funded by many additional sources (AIMS CDT, Cyber CDT, industry, and more). If you'd like to join us take a look here.

Current group members: Yarin Gal (Associate Professor) ● Freddie Kalaitzis (Senior Research Fellow, 2020) ● Neil Band (MSc by Research, 2020) ● Mizu Nishikawa-Toomey (Research Assistant, 2020) ● Atılım Güneş Baydin (Associate Member (Faculty), 2020) ● Gabriel Jones (Associate Member (PhD), 2020) ● Tuan Nguyen (Associate Member (PhD), 2020) ● Lisa Schut (PhD, 2020) ● Jannik Kossen (PhD, 2020) ● Jan Brauner (PhD, 2020) ● Muhammed Razzak (PhD, 2020) ● Andrew Jesson (PhD, 2019) ● Jishnu Mukhoti (PhD, 2019) ● Sören Mindermann (PhD, 2019) ● Tom Rainforth (Associate Member (Faculty), 2019) ● Pascal Notin (PhD, 2019) ● Panagiotis Tigas (PhD, 2019) ● Aidan Gomez (PhD, 2018) ● Joost van Amersfoort (PhD, 2018) ● Clare Lyle (PhD, 2018) ● Binxin (Robin) Ru (PhD, 2018) ● Tim G. J. Rudner (PhD, 2018) ● Angelos Filos (PhD, 2018) ● Andreas Kirsch (PhD, 2018) ● Lewis Smith (PhD, 2017) ● Sebastian Farquhar (PhD, 2017) ● Milad Alizadeh (PhD, 2017)

Group Invited Talks

Recent invited talks:
16 Mar 2021, 15:00, Zoom Debbie Marks (Harvard).
09 Mar 2021, 15:00, Zoom Greg Yang (Microsoft Research). Feature Learning in Infinite-Width Neural Networks
02 Mar 2021, 14:00, Zoom Uri Shalit (Technion - Israel Institute of Technology). Causality-Inspired Machine Learning
23 Feb 2021, 17:00, Zoom Adi Hanuka (SLAC National Laboratory, Stanford). Machine learning for Design and Control of Particle Accelerators

Group Collaborators and Affiliates

Our group collaborators include:

And our group affiliates include:

Are you looking to do a PhD in machine learning? Did you do a PhD in another field and want to do a postdoc in machine learning? Would you like to visit the group?

How to apply


We are located at
Department of Computer Science, University of Oxford
Wolfson Building
Parks Road
Twitter: @OATML_Oxford
Github: OATML