Building a community
Led by Oxford, the hub network consists of six academic institutions spanning the UK, bringing together leading researchers in mathematics, algorithms, and computing. The research programme aims to remove barriers between fields and unify a diverse cohort, exploiting tools from currently underexplored mathematical fields to understand and advance AI. The hub also aims to attract theoreticians to new problems and applications in AI in both scientific and industrial settings.
The work of the hub aims to bring a transformative cross-fertilisation of expertise and ideas, forming new interdisciplinary partnerships, and establishing long-term capability that will underpin the future of AI and the UK’s AI ecosystem. It will engage mathematicians across a range of fields as it opens a gateway to new problems, applications, opportunities, and collaborations. It will also support and influence research in machine learning and AI, offering an influx of new expertise, ideas, and tools. Our partnerships with industry leaders will also forge unique commercial links and advance the expertise and application of mathematics in AI across the economy and society.
Comprising six nodes at universities across the UK, the hub is headed by Professor Michael Bronstein at the University of Oxford, Dr Anthea Monod at Imperial College London, and Professor Jeffrey Giansiracusa at Durham University. The team will head an ambitious research programme, driven forward by a diverse cohort of Postdoctoral Research Associates (PDRAs) and PhD students across the hub network.
Meet our team
Prof Michael Bronstein
Hub Co-Director, Principal Investigator
University of Oxford
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.
Dr Anthea Monod
Hub Co-Director, Imperial Lead
Imperial College London
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.
Prof Jeffrey Giansiracusa
Hub Co-Director, Durham Lead
Durham University
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.
Prof Heather Harrington
Co-Investigator, Oxford Lead
University of Oxford
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.
Prof Primoz Skraba
Co-Investigator, QMUL Lead
Queen Mary University of London
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).
Prof Jacek Brodzki
Co-Investigator, Southampton Lead
University of Southampton
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).
Prof Ran Levi
Co-Investigator, Aberdeen Lead
University of Aberdeen
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.
Prof Omer Bobrowski
Co-Investigator, Theme A Lead
Queen Mary University of London
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).
Dr Yue Ren
Co-Investigator, Theme B Lead
Durham University
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.
Prof Jared Tanner
Co-Investigator, Theme C Lead
University of Oxford
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.
Prof Alessandro Abate
Co-Investigator, Theme D Lead
University of Oxford
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.
Prof Gesine Reinert
Co-Investigator, Oxford Statistics Lead
University of Oxford
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.
Prof Peter Grindrod
Co-Investigator, Industry Engagement Lead
University of Oxford
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.
Prof Ulrike Tillman
Co-Investigator, Theme A Deputy Lead
University of Oxford
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.
Prof Coralia Cartis
Co-Investigator, Theme B Deputy Lead
University of Oxford
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.
Prof Marika Taylor
Co-Investigator, Theme C Deputy Lead
University of Southampton
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.
Prof Tom Coates
Co-Investigator, Theme D Deputy Lead
Imperial College London
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.
Prof Sam Cohen
Co-Investigator
University of Oxford
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.
Prof Giuseppe De Giacomo
Co-Investigator
University of Oxford
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.
Dr Haim Dubossarsky
Co-Investigator
Queen Mary University of London
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.
Prof Marta Kwiatkowska
Co-Investigator
University of Oxford
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.
Prof Marc Lackenby
Co-Investigator
University of Oxford
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.
Prof Jeroen Lamb
Co-Investigator
Imperial College London
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.
Prof Renaud Lambiotte
Co-Investigator
University of Oxford
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.
Prof Terry Lyons
Co-Investigator
University of Oxford
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.
Prof Mahesan Niranjan
Co-Investigator
University of Southampton
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.
Prof Harald Oberhauser
Co-Investigator
University of Oxford
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.
Prof Dave Parker
Co-Investigator
University of Oxford
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.
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.
Prof Norbert Peyerimhoff
Co-Investigator
Durham University
Norbert is a Mathematician working in spectra and dynamics in discrete and differential geometry and applications to X-ray crystallography, robotics and AI.
Prof Patrick Rebeschini
Co-Investigator
University of Oxford
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.
Prof Justin Sirignano
Co-Investigator
University of Oxford
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.
Dr Ruben Sanchez-Garcia
Co-Investigator
University of Southampton
Ruben works in network science and applied topology, including applications of topological data analysis to image analysis and ML.
Postdoctoral Research Associates
Dr Thom Badings
University of Oxford
Thom is a Postdoctoral Research Associate with the Oxford Control and Verification Group at the University of Oxford. He obtained his doctoral degree (cum laude) from Radboud University in Nijmegen, the Netherlands. His research interests lie broadly on the intersection between control theory, artificial intelligence, and formal verification. With his research, Thom aims to develop techniques that can be used to provide rigorous mathematical guarantees about the safety and reliability of complex and uncertain systems.
Dr Oliver Clarke
Durham University
Oliver is a Postdoctoral Research Associate at Durham University working on the foundations of Non-Archimedean Optimisation and Machine Learning. His aim is to develop state-of-the-art algorithms for hierarchical data, such as trees or genetic data, by using tools from Tropical Geometry. Oliver’s background is in Algebraic/Tropical Geometry, Combinatorics, and their applications.
Dr Francesco Fabiano
University of Oxford
Francesco is a Research Associate at the Department of Computer Science, University of Oxford. He is also a Research Fellow at Saint Joseph’s University, affiliated faculty at New Mexico State University, and part of IBM’s cognitive AI research group. His work focuses on human decision-making, considering factors like experience, task relevance, and cognitive biases, to design AI systems that emulate human reasoning. He also researches knowledge and belief representation in multi-agent systems, with a strong emphasis on neuro-symbolic AI, epistemic reasoning, and computational logic.
Dr Eng-Jon Ong
Queen Mary University of London
Eng-Jon recently joined the School of Mathematical Sciences at Queen Mary University of London and is working on applying topological data analysis methods to better understand how DNNs function and learn. His main interests are in visual feature tracking, data mining, pattern recognition, and theoretical machine learning methods. He is interested in how probability distributions propagate through deep neural network layers. He has also applied deep neural networks (DNNs) in the area of medical imaging.
Dr Edward Pearce-Crump
Imperial College London
Edward is a Postdoctoral Research Associate in the Erlangen AI Hub at Imperial College London, working on the mathematical and computational foundations of AI. His research spans group equivariant neural networks, category theory, algebraic combinatorics, and quantum computing. He holds a PhD in Computer Science from Imperial, where he was awarded a G-Research PhD Prize for his thesis. He is especially interested in using abstract mathematical structures to design practical machine learning architectures.