Hub Directors and Co-Investigators

Michael is DeepMind Professor of AI at the University of Oxford, Founding Scientific Director, AI at the Aithyra Institute in Vienna, and Turing AI World-Leading Research fellow. He was previously Head of Graph Learning Research at Twitter, a professor at Imperial College London and held visiting appointments at Stanford, MIT, and Harvard. Michael has more than a decade of experience in big tech and start-up companies.

Anthea works in adapting algebraic topology and algebraic geometry to data analysis, statistics, and theoretical machine learning, with a focus on feasible, interpretable, and computationally efficient methods.  Her fields of research are applied and computational topology (including topological data analysis), applied and computational algebraic geometry (including algebraic statistics), and geometric deep learning.

Jeffrey has made broad contributions across topology, tropical geometry, and data-driven techniques in computational statistical physics. He leads the Durham node of the Centre for TDA and was Mathematics lead for the EPSRC CDT in Human-Centred AI at Swansea. Jeffrey has over a decade of experience driving EDI and currently leads Durham Mathematics’ Athena SWAN SAT.  

Heather is an applied mathematician and co-founder of the UK Centre for TDA. She is a Royal Society University Research Fellow, and former Turing Institute Fellow. Her research has been recognised by Whitehead, Adams and Leverhulme Prizes.  

Primoz works in applied and computational topology. Previously he was a member of the AI Department at the Jozef Stefan Institute, Slovenia, overseeing multiple EU and industrial projects on applications of AI and ML in areas such as energy, finance, and government (policy).

Jacek Brodski is an expert in Topological Data Analysis, Mathematical Foundations of AI, applications of Topology in Physics, Medicine, Engineering, as well as in Noncommutative Geometry. He established and leads a research group in Topological Data Analysis funded by the EPSRC (Joining the Dots: From data to insight, £1.2M, Mathematical Foundations of Intelligence: An “Erlangen Programme for AI”, £1.4M Southampton, part of a £10M consortium).

Ran works in pure and applied algebraic topology and applications in neuroscience, medical imagine and ecology. He held an EPSRC grant Topological Analysis of Neural Systems and a collaboration grant with the Blue Brain Project. His approach to natural and artificial neural networks combines graph theory, combinatorics, algebra and topology. Ran was an invited speaker at the 2018 Abel symposium and is regularly invited to present in national and international conferences.  

Omer works on random topology and its applications. He has made significant contributions to the development of probabilistic and statistical theories that underpin the methodologies employed in Topological Data Analysis (TDA). 

Yue is a UKRI Future Leaders Fellow and leading expert in tropical geometry, mathematical software, and the application of both to neural networks and problems in industry and sciences. He is a core developer of the computer algebra systems Polymake, Singular, and OSCAR. 

Jared is an expert in the mathematics of information, recognised by a Sloan Fellowship and Martin and Leverhulme Prizes. He was one of the initial Turing University Directors.

Alessandro tackles scientific challenges in the area of safe AI and assured autonomy. Technically, his research interests lie in the formal verification and optimal control of heterogeneous and complex dynamical models, built from first principles or learnt from data. Alessandro blends in techniques from machine learning and AI, such as Bayesian inference, RL, and game theory. 

Gesine is an expert in network analysis and in probabilistic approximations and underpinnings of machine learning procedures. She is a Fellow of the IMS and recipient of an EPSRC Established Career Fellowship.   

Peter is an applied mathematician and entrepreneur, ex-President of IMA, and member of the MOD’s DSAC. He has served on the councils of EPSRC and BBSRC, contributes to Government policy and strategy initiatives on AI, has written on ethics and responsible research for data and AI, was a founding trustee of the Turing Institute, and has founded numerous start-ups. 

Ulrike is a Topologist and co-founder of the UK Centre for TDA. She received an EPSRC Advanced Fellowship, the Whitehead and Bessel Prizes, and was elected to the Royal Society, the German National Academy (Leopoldina) and the European Academy of Sciences as well as a Fellow of the AMS and IMA. Ulrike is a former Turing Institute Faculty Fellow and inaugural Chair of its Programme Committee, President of the LMS and presently Director of the Newton Institute, Cambridge.  

Coralia is Professor of Numerical Optimization at the Mathematical Institute, University of Oxford and a Fellow of Balliol College. She has been a long-standing Turing Fellow (2016-2024) at The Alan Turing Institute for Data Science, London. Coralia’s research interests include the development, analysis, and application of nonlinear optimization algorithms.

Marika is a Professor of Mathematics, Physics and AI. She trained in theoretical physics under Stephen Hawking, and is currently interested in geometric ML for fundamental physics applications and physics-inspired methods for ML. Marika was a Turing Institute Fellow and recipient of the “Dutch ERC” Vidi. She has a long track record with start-ups, including in encryption and fintech.  

Tom is a mathematician combining fundamental research in geometry with cluster-scale computation, data mining, and ML. He is currently on secondment to the Office of the Chief Scientific Adviser and a member of the Executive Committee developing the Academy for the Mathematical Sciences, with responsibility for Early Career and EDI. Tom is a multiple ERC grantee. 

Sam is Professor of Mathematics in the Mathematical Institute, and fellow of New College. He completed his undergraduate and doctoral studies in mathematics and finance at the University of Adelaide, before moving to Oxford in 2010. His research revolves around the mathematics of probability, statistical estimation methods, decision making, and modelling in finance other application areas. In particular, he is interested in how the uncertainty due to statistical estimation should affect decision making, and how to implement this in practical situations.

Rama is Professor of Mathematics at Oxford’s Mathematical Institute, Head of the Mathematical & Computational Finance Group, and a Fellow of St Hugh’s College. He is the Director of the Centre for Doctoral Training in Mathematics of Random Systems. His research topics include stochastic computational methods, mathematical foundations of AI, generative models and data-driven modelling in finance. Rama has been scientific advisor to several AI-focused start-ups, including InstaDeep, 73Strings and Synthera.AI. 

Giuseppe is a Professor of Computer Science at the University of Oxford and a Governing Body Fellow at Green Templeton College. He was previously a Professor at the Department of Computer, Control, and Management Engineering of the University of Roma “La Sapienza”. Giuseppe is an AAAI Fellow, ACM Fellow, and EurAI Fellow. He received an ERC Advanced Grant for the project WhiteMech: White-box Self Programming Mechanisms. He is on the Board of EurAI. 

Haim is a computer scientist and NLP expert whose work focuses on the information that can be extracted from the parameters of Large Language Models (LLMs), such as bias, word meaning change, and other linguistic information.

Raphael is an Associate Professor in Mathematical Programming at the Oxford Mathematical Institute and the Tanaka Fellow in Applied Mathematics at Pembroke College Oxford. His research interests lie at the interface between complexity theory, optimisation algorithms, probability theory and data science. Notable achievements include the award of the SIAM Activity Group on Optimization Prize, as well as serving on the editorial boards of several journals in mathematical optimisation.

Varun is interested in all aspects of machine learning theory. He has worked on computational learning theory, including agnostic learning, boosting, reliable learning, and fair learning. Varun has also worked on optimisation algorithms for learning and identifying computational and statistical tradeoffs. More recently, he has worked on modern ML models and foundation models to understand their properties from a mathematical standpoint.

Marta is an expert in formal methods for analysis and verification of complex ML/AI systems. She received the Lovelace Medal, Milner Award, and multiple ERC grants. 

Marc is a Professor at the University of Oxford. He has been a recipient of an LMS Whitehead Prize (2003), a Leverhulme Prize (2006) and a Frontiers in Science Awards (2024), and was an Invited Speaker at the 2010 International Congress of Mathematicians. Marc specialises in low-dimensional topology, hyperbolic geometry and group theory. He is interested in using machine learning as a tool for pure mathematicians. He has also been developing novel architectures for neural networks.

Jeroen is an expert in deterministic and random dynamical systems, equivariant and symplectic learning, and the dynamics of ML algorithms. He was an EPSRC Advanced Research Fellow and led the European research consortia BREUDS and CRITICS. Jeroen is currently on the management board of the CDT Mathematics of Random Systems.

Renaud is a Professor of Networks and Nonlinear Systems at the University of Oxford. His research focuses on complex systems, network theory, and data-driven modelling of social and brain dynamics. He is recognised for his work on community detection, temporal networks, and the mathematical analysis of collective behaviour.

Terry is an expert in stochastic analysis, known for work on rough paths and universal approximation in neural networks. He received Whitehead and Polya prizes and served as President of the LMS. 

Mahesan has more than 30 years of experience in theoretical and applied ML, and was previously Head of Computer Science and Dean of Engineering at Sheffield.  

Harald is a Professor in the Mathematical Institute at the University of Oxford and a Tutorial Fellow at St Hugh’s College. He obtained his PhD from the Statslab at the University of Cambridge. He works on topics that connect recent progress in pure mathematics with real world applications.

Dave is a Professor of Computer Science at the University of
Oxford. His research is in formal verification, with a particular focus
on the analysis of probabilistic systems, and he leads the development of the widely used verification tools PRISM and PRISM-games. Dave’s current research interests include verification techniques for applications in AI and machine learning, including robust methods for quantifying uncertainty and game-theoretic approaches.

Norbert is a Mathematician working in spectra and dynamics in discrete and differential geometry and applications to X-ray crystallography, robotics and AI.  

Patrick is Professor of Statistics and Machine Learning in the Department of Statistics at the University of Oxford. His research focuses on uncovering and leveraging fundamental principles in high-dimensional probability, statistics, and optimisation to develop computationally efficient and statistically optimal algorithms for machine learning and artificial intelligence.

Christoph is Professor of Applied Mathematics and an expert on stochastic simulation and control, mean-field models, and mathematical foundations of deep learning. He currently collaborates with industry and government in the areas of AI security, air traffic control, and financial market microstructure. Within the hub, Christoph’s fundamental research lies at the interface of control and reinforcement learning.

Justin is a Professor of Mathematics at the University of Oxford, where he is a researcher in the areas of Applied Mathematics, Machine Learning, and Financial Mathematics. He is faculty member in the Mathematical & Computational Finance, Machine Learning & Data Science, and Oxford Centre for Industrial & Applied Mathematics (OCIAM) research groups at the Mathematical Institute. 

Ruben works in network science and applied topology, including applications of topological data analysis to image analysis and ML.