OATML

Yarin leads the Oxford Applied and Theoretical Machine Learning (OATML) group. He is an Associate Professor of Machine Learning at the Computer Science department, University of Oxford. He is also the Tutorial Fellow in Computer Science at Christ Church, Oxford, and a Turing Fellow at the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence. Prior to his move to Oxford he was a Research Fellow in Computer Science at St Catharine’s College at the Uni...

Tom is a researcher in statistical machine learning at the University of Oxford. His research covers a wide range of topics including probabilistic programming, Monte Carlo methods, variational inference, experimental design, and deep generative models. He is a part-time senior postdoc with the OATML research group, and a junior research fellow at Christ Church college.

Challenger is a theoretical physicist working on the long-standing problem of quantising gravity. Recently, he started to undertake work in Theoretical Machine Learning, in order to exploit its tools to understand String Theory as a problem in big data. As a Rhodes Scholar he has pursued his passion in understanding fundamental physical processes by undertaking doctoral work in String Theory at the Rudolf Peierls Centre for Theoretical Physics, University of Oxford. During his recently compl...

Lisa Schut is a research assistant in the OATML group, supervised by Yarin Gal. Her main interests are centered around making machine learning algorithms more robust and interpretable. Lisa holds two master’s degrees, in Statistics and Computer Science, from the University of Oxford. Previously, Lisa was a member of the Dutch women’s Olympic chess team.

Oscar is a research assistant in the OATML group at the University of Oxford. Previously he completed a master’s degree in computer science at Oxford. During this, he worked in the group on his dissertation, a comparison of uncertainty estimates for safe exploration in machine learning. Before coming to Oxford he spent two years at Google, having received an undergraduate degree in computer science from the University of Cambridge.

Sören is a DPhil student in CS supervised by Yarin Gal from OATML and Allan Dafoe from Oxford’s Centre for the Governance of AI. His interests in machine learning include its economic and political properties, how it scales, and safety. Before joining OATML, he worked on reward inference and machine learning for game theory with David Duvenaud and Roger Grosse at Toronto’s Vector Institute, with the Center for Human-compatible AI at UC Berkeley, and at the Future of Humanity Institute at Oxfo...

Jishnu is a DPhil (PhD) student at the University of Oxford working with Philip Torr and Yarin Gal. He is interested in ways by which approximate Bayesian inference can be performed in a scalable, light-weight manner in deep neural networks. He previously worked at Amazon as a Software Developer and also did his MSc in Computer Science at Oxford.

Panos is a DPhil student in the OATML group in the Department of Computer Science at the University of Oxford, supervised by Yarin Gal. He is interested in representation learning for control and communication, in single and multi-agent systems. Prior to his DPhil he worked as software engineer for Microsoft (Relevance/NLP), Autodesk (AI/Generative Design), Brave (Privacy Preserving ML) and his own startup Filisia (Special Education Tech). He has an MSc in Machine Learning from University of ...

Andrew is a DPhil student in the Department of Computer Science at the University of Oxford. He works in the Applied and Theoretical Machine Learning Group (OATML) under the supervision of Yarin Gal. Prior to joining the group, he was a program manager and researcher at Imagia in Montreal. He obtained his undergraduate and master’s degrees from the Department of Electrical and Computer Engineering at McGill University, working in the Probabilistic Vision Group (PVG) with Tal Arbel. He is inte...

Pascal is a DPhil student in the CS Department at Oxford University, supervised by Yarin Gal. He is interested in advancing existing machine learning approaches to transform health care via more robust and interpretable models. He has several years of applied machine learning experience developing AI solutions within the pharmaceutical and financial industries. He obtained a master’s degree in Operations Research from Columbia University and undergraduate degree in Applied Mathematics at Ecol...

Clare is a DPhil student at the University of Oxford working with Yarin Gal and Marta Kwiatkowska. She has previously worked on developing a stronger theoretical understanding of distributional reinforcement learning at Google Brain, and is broadly interested in theoretical foundations of machine learning. She obtained her undergraduate degree in mathematics and computer science at McGill University, and is a Rhodes Scholar.

Aidan is a doctoral student of Yarin Gal and Yee Whye Teh at The University of Oxford. He leads a research group, called FOR.ai, focussing on providing resources, mentorship, and facilitating collaboration between academia and industry. Aidan’s research deals in understanding and improving neural networks and their applications. Previously, he worked with Geoffrey Hinton and Łukasz Kaiser on the Google Brain team. He obtained his Bachelors from The University of Toronto with supervision from ...

Andreas is a 2nd-year DPhil with Yarin Gal in the AIMS program. He is interested in Bayesian Deep Learning, and ethics and safety in AI. Before joining OATML he worked at DeepMind in London as a research engineer and for Google/YouTube in Zurich as a software engineer. He studied computer science and maths at the Technical University in Munich. While originally from Romania, he grew up in Southern Germany. He likes schnitzel, sarmale, bouldering and running. He is a Clarendon Scholar.

Angelos is a DPhil student in the Department of Computer Science at the University of Oxford, where he works in the Applied and Theoretical Machine Learning group (OATML) under the supervision of Yarin Gal. His research interests span multi-agent systems, meta-learning and reinforcement learning. He obtained an undergraduate and master’s degree from the Department of Electrical and Electronic Engineering at Imperial College London. He also contracts with J.P. Morgan Artificial Intelligence Re...

Joost is a DPhil student in the OATML group in the Department of Computer Science at the University of Oxford, supervised by Yarin Gal and Yee Whye Teh. He is interested in representation learning, variational inference, and Bayesian methods. Furthermore he likes to play with new programming languages for ML, such as Swift and Julia. Previously, he spent two years at Twitter Cortex as part of the team that came out of the Magic Pony acquisition. He obtained his MSc. at the University of Amste...

Milad is a DPhil student in the Computer Science department at the University of Oxford, where he works in the Machine Learning Systems Group (OX-MLSYS) under the supervision of Nic Lane and Applied and Theoretical Machine Learning Group (OATML) with Yarin Gal. Prior to joining the University of Oxford, he was a Senior Software Engineer at Qualcomm Technologies in Cambridge, and Imagination Technologies in Bristol. He received his MSc in Digital Signal Processing from University of Bristol in...

Seb is a DPhil student supervised by Yarin Gal and part of the Centre for Doctoral Training in Cyber Security. He is interested in the pragmatic fundamentals of deep learning for their own sake as well as for their application to safe and secure machine learning systems. Before joining the research group, he worked in technology policy (including biosafety and AI policy), social-entrepreneurship, and strategy consulting. He has been working on startups in the effective altruism community sinc...

Tim is a DPhil student in the Department of Computer Science at the University of Oxford, working with Yarin Gal and Yee Whye Teh. His research interests span Bayesian deep learning, variational inference, and reinforcement learning. Tim obtained a master’s degree in statistics from the University of Oxford and an undergraduate degree in mathematics and economics from Yale University, where he received the Charles E. Clark Memorial Award for Academic Excellence. He is an AI Fellow at Georgeto...

Lewis Smith is a DPhil student supervised by Yarin Gal. His main interests are in the reliability and robustness of machine learning algorithms, Bayesian methods, and the automatic learning of structure (such as invariances in the data). He is also a member of the AIMS CDT. Before joining OATML, he recieved his masters degree in physics from the University of Manchester.

Zac was a Postdoc in OATML working with Yarin Gal. His primary research interest is technical AI safety, and is currently working on robustness and safe exploration in reinforcement learning. He was previously a Research Assistant with Owain Evans at the Future of Humanity Institute, University of Oxford and a Visiting Researcher at the Montreal Institute for Learning Algorithms (MILA), under Yoshua Bengio. He also worked as a Data Scientist at ASI Data Science. He completed his PhD at Queen ...