In the latest of the hub’s seminar series, Raphaël Tinarrage of the Institute of Science and Technology Austria visited Imperial College London on 11 November to give a talk on Linear orbits of compact Lie groups and machine learning.
When a problem involves continuous symmetries, such as rotations, one naturally expects a Lie group action. In some cases, this action is linear, that is, made of rigid Euclidean motions. As a matter of fact, linear actions arise in several corners of data analysis: in image processing, where standard embeddings commute with Euclidean isometries; in equivariant neural networks, where one structurally forces linear actions or favors them via optimization; or in physical systems, where representations are found sometimes through Noether’s theorem, and sometimes more unexpectedly.
However, most of the time, the representation is not observed directly, but only through its orbits. Recovering the underlying representation from a single orbit would not only allow one to verify the Lie linear orbit hypothesis, but also to improve existing data analysis techniques.
In his talk, Raphaël presented such an orbit-regression algorithm, developed with Henrique Ennes, PhD student at the Inria Centre at the Université Côte d’Azur. Building on previous work by Cahill, Mixon and Parshall, they tackle the problem at the level of Lie algebras, where it can be reformulated as a discrete-continuous optimization over the orthogonal group. In addition to presenting the algorithm and its theoretical guarantees, Raphaël’s talk also delved into the applications mentioned above.
City St George’s, University of London, played host to a highly successful Topological Data Analysis seminar supported by the Erlangen AI Hub, in association with the London Mathematical Society, on 6-7 November.
The London – Oxford – Paris TDA Seminar, whose organising team included Hub Co-Director Anthea Monod and Hub Co-I Omer Bobrowski of Imperial College London (pictured left and centre above), brought together researchers from across the UK and France working in and around the field of algebraic topology, geometry and topological data analysis.
This special edition of the seminar included a number of high profile speakers, including academics from École Polytechnique, University of Oxford, Imperial College London, King’s College London, University of Southampton, Jussieu Institute of Mathematics, and Northeastern University London.
Xinyu Li, a new Postdoctoral Research Associate based at Oxford’s Mathematical Institute, delivered the latest in the hub’s seminar series on 23 October. The seminars provide a great opportunity for the newest members of the hub’s teams to present their research to the community.
Xinyu’s talk, entitled Markov α-Potential Games: A Framework to study Multi-Agent Reinforcement Learning, proposed a new framework of Markov α-potential games to study Markov games. It showed that any Markov game with finite-state and finite-action is a Markov α-potential game, and established the existence of an associated α-potential function. Any optimizer of an α-potential function is shown to be an α-stationary Nash equilibrium.
Xinyu studied two important classes of practically significant Markov games, Markov congestion games and the perturbed Markov team games, via the framework of Markov α-potential games, with explicit characterisation of an upper bound for α and its relation to game parameters. She also provided a semi-infinite linear programming-based formulation to obtain an upper bound for α for any Markov game. Furthermore, Xinyu studied two equilibrium approximation algorithms, namely the projected gradient- ascent algorithm and the sequential maximum improvement algorithm, along with their Nash regret analysis.
Our hub members have been kindly answering a set of questions so that we can share more about them and their work. We start with Hub Co-Director Jeffrey Giansiracusa of Durham University.
Can you share a bit about your background and your current research focus? I started off as a very pure mathematician, working in topology and homotopy theory. From there I drifted towards algebraic aspects of tropical geometry, but over the past 5 years I’ve become increasingly interested in applications of topological data analysis to quantum field theory data, as well as machine learning in non-archimedean and tropical geometry.
What inspired you to pursue this area? By now I’ve worked in several very different areas of mathematics. In each case it was the incluence of mentors and a supportive community that brought me into learning and doing new things.
Which themes are you connected to within the Erlangen AI Hub? Theme A: Understanding Data Theme B: Understanding Machine Learning Models
What attracted you to the Erlangen AI Hub and what do you hope to see it achieve? As one of the architects of the hub, I was very excited about the opportunity to help develop the already impressive community of people in the UK doing topological data analysis, encouraging them to connect to ML and AI and some of the really big questions around right now.
What’s been the most surprising or exciting finding in your work so far? Gradient descent optimisation shouldn’t work in a non-archimedean setting, where small steps can’t add up to a big step. But we found a non-archimedean optimisation procedure that looks a lot like gradient descent which does work!
What challenges have you faced in your research, and how did you overcome them? My biggest challenge is always balancing my various projects and responsibilities, and balancing work with family commitments. I often have to leave meetings early to collect my kids from school and take them to their various activities.
What advice would you give to someone just starting out in your field? Find the people you enjoy working with, and then work with them! Don’t waste your time working with people that you don’t like.
What’s something people might be surprised to learn about you outside of research? My favourite person to do mathematics with is my brother.
Two Imperial PhD graduates under the tutelage of Hub Co-Director Anthea Monod have secured key postdoctoral positions at leading research institutions in Europe.
Inés Garcia-Redondo (pictured left) successfully completed her PhD and begins postdoctoral life as Senior Researcher at the AIDOS (AI for Data-Oriented Science) Lab at the University of Fribourg, led by Professor Bastian Rieck, whose work is closely aligned with the mission of the hub. Inés’ research focuses on topological data analysis, particularly in its use within machine learning systems, to investigate the mathematical foundations of AI. She said:
“I intend to continue my research at the interface of topology and geometry, and deep learning systems, which I initiated with Anthea as a student aligned to the hub. I’m very grateful and excited for the new opportunities to come, and to stay connected to the hub as well!”
Meanwhile, Yueqi Cao (pictured right) has been awarded a Digital Futures Postdoc Fellowship at the Department of Mathematics at KTH Royal Institute of Technology in Stockholm, supervised by Profs Johan Karlsson and Sandra Di Rocco. Yueqi’s research sits at the crossroads of mathematics, statistics, and machine learning. During his PhD, he developed new tools and methods to analyse metric graphs using ideas from tropical geometry and topological data analysis. Yueqi’s postdoctoral research will now see him extend his research in metric graphs, exploring new geometric and topological methods and applications in machine learning and data analysis. He said:
“I am excited to embark a new postdoctoral position at KTH, where I look forward to further developing my research and building new collaborations, and making new connections in Europe to advance the research areas of the hub, strengthening connections between pure mathematics, computation, and machine learning.”
Congratulations to Ines and Yueqi. We wish them the best of luck in their new roles!
It’s conference season and hub members have been busy presenting work across the world. Take a look at a snapshot of activity below:
UK AI Research Symposium – September 2025, Northumbria University
Hub members took part in a fantastic two days at the UK AI Research Symposium (UKAIRS) at Northumbria University.
Congratulations to Oliver Clarke, Edward Pearce-Crump and Qiquan Wang, who presented their research during the poster sessions, and Edward who also gave a lightning talk on his research.
UKAIRS was a hugely inspiring event bringing together and consolidating the UK’s AI research community, with highly engaging talks, demos, panels, posters and keynotes across diverse disciplines, with reflections on the future of AI and emerging challenges. It was also a brilliant platform for our postdocs to showcase their research and meet peers from across the UK, facilitating connections and ideas-sharing with the wider AI research community, including the other EPSRC AI hubs. Many thanks to organisers Responsible Ai UK and the steering committee for their hard work putting the event together.
Applied Algebraic Topology Research Network (AATRN) conference – August 2025, Chicago
Several hub members attended a week-long conference in celebration of the 10-year anniversary of AATRN, the Applied Algebraic Topology Research Network, at the Institute for Mathematical and Statistical Innovation in Chicago.
Speakers included hub members Anthea Monod, Omer Bobrowski and Heather Harrington. They were accompanied by hub PhD students Arne Wolf, Inés Garcia-Redondo and David Lanners.
The event was AATRN’s first in-person meeting, bringing together researchers from mathematics, statistics, computer science, physics, biology, and beyond.
Anthea Monod was a speaker at the Graph Learning Meets Theoretical Computer Science workshop (co-chaired by Michael Bronstein) at the Simons Institute for the Theory of Computing at the University of California, Berkeley. She offered a Bootcamp on geometry and graph learning.
The workshop brought together researchers to provide a more unified perspective on graph learning within theoretical computer science.
International Joint Conference on Artificial Intelligence (IJCAI) – August 2025, Montreal
Guiseppe De Giacomo presented three papers at the International Joint Conference on Artificial Intelligence (IJCAI) 2025 in Montreal.
SIAM (Society for Industrial and Applied Mathematics) conference – July 2025, Wisconsin
During the summer, Oliver Clarke presented his work at the SIAM (Society for Industrial and Applied Mathematics) 2025 Conference on Applied Algebraic Geometry in Madison, Wisconsin.
The SIAM Activity Group on Algebraic Geometry has a broad scope and brings together researchers using tools in commutative algebra, geometry, topology, combinatorics, computational algebra to solve ‘applied problems’ in areas such as biology, computer vision, machine learning, robotics, and statistics. The SIAM AG conference, which takes place every 2 years, is a chance to see what fellow researchers are working on through a series of parallel mini-symposia and plenary talks.
Oliver presented his work-in-progress alongside Yue Ren, Jeffrey Giansiracusa, and Julio Quijas-Acaves, with a talk entitled Towards non-Archimedean Machine Learning. The project is concerned with developing machine learning tools, for instance gradient descent, over non-Archimedean fields such as the p-adics. Oliver said:
“I was delighted with the attendance for my talk, presenting to a packed seminar room, which lead to fruitful conversations with experts in p-adics analysis and tropical geometry.”
The conference lasted 5 days, during which time Oliver attended around 50 talks, learning about many of the problems and techniques in applying algebraic geometry to machine learning. He added:
“It was an excellent opportunity and I’m looking forward to presenting some concrete results in the future.”
International Conference on Machine Learning (ICML) – July 2025, Vancouver
A team of researchers including Michael Bronstein won the best paper award at the ICML Generative AI and Biology (GenBio) workshop for FORT: Forward-Only Regression Training of Normalizing Flows.
Uzu Lim presented Cover Learning for Large-Scale Topology Representation at ICML. Authors of the joint paper also included Luis Scoccola and Heather Harrington, the hub’s Oxford Maths lead.
Edward Pearce-Crump (pictured above) presented his work Permutation Equivariant Neural Networks for Symmetric Tensors at ICML. Edward said:
“I’m delighted to have had the opportunity to present my work at ICML 2025 in Vancouver! The feedback I received was incredibly valuable and will guide me in my future research. It was also a pleasure to see old colleagues again and engage in thoughtful discussions about the latest advances in AI.”
Doctoral student Thiziri Nait Saada presented work supported by the hub at ICML. Mind the Gap: a Spectral Analysis of Rank Collapse and Signal Propagation in Attention Layers was authored by Thiziri alongside Alireza Naderi and Jared Tanner.
International Conference on Computer-Aided Verification (CAV) – July 2025, Zagreb
Thom Badings (pictured above) presented his work at CAV in July.
In the joint paper Policy Verification in Stochastic Dynamical Systems Using Logarithmic Neural Certificates his team developed novel techniques for the verification of neural network policies in stochastic dynamical systems.
The Erlangen AI Hub was a ‘diamond’ sponsor of the 2025 London Geometry and Machine Learning (LOGML) Summer School at Imperial College London this year.
Every July the summer school brings together mathematicians and computer scientists to collaborate on a range of problems at the intersection of geometry and machine learning. The week-long event features a number of group projects, each overseen by an experienced mentor, talks by leading figures in the field, a poster session, networking with industry, and social events.
As a primary sponsor, the Erlangen AI Hub enjoyed a key presence at this year’s school, with many members, hub-aligned postdocs and PhD students involved as organisers, advisors, project leaders, and participants. The organising team included incoming hub-aligned Postdoctoral Research Associate Daniel Platt and hub-aligned PhD student Arne Wolf. The scientific advisory board included Dr Anthea Monod, Prof Heather Harrington, and Prof Michael Bronstein, one of the original founders of the school during his time at Imperial.
This year’s vibrant and fruitful event welcomed more than 100 participants from across the world, who collaborated in teams on 19 mentored projects and enjoyed a range of talks and tutorials from high profile speakers including the hub’s Prof Coralia Cartis. It wasn’t all work though as attendees enjoyed a range of social activities including a welcome breakfast at the V&A Museum, a company night, bouldering, live music, and lunch at Chiswick House and Gardens.
Co-Director of the Erlangen AI Hub, Dr Anthea Monod, was a key advisor to the summer school and co-led a project with fellow hub board member Prof Omer Bobrowski. Anthea said:
“It was a fantastic, first-class summer school, and I am proud of the hard work of the organisers. I had the pleasure of leading a project using topology to study the evolution of high dimensional neural activation patterns. It was so much fun and great to catch up with people on the circuit. Huge thanks to the Erlangen AI Hub for being a diamond sponsor.”
When the EPSRC announced £100 million in funding for nine new AI research hubs in 2024, the Erlangen AI Hub took its first steps from a lofty concept towards becoming one of the UK’s foremost research hubs, using mathematical principles to inform the next generation of AI. Now in its second year, as the hub’s rapid evolution continues, it is establishing itself at the front and centre of the UK’s AI landscape, defining the way we understand and use AI.
The Erlangen AI Hub draws inspiration from Felix Klein’s Erlangen Programme, which brought a revolutionary, unifying perspective to geometry and symmetry in the 19th and 20th Centuries. True to its namesake, the hub has been working to consolidate disparate elements of mathematics, algorithms, and computing, harnessing classical theories and encouraging new ones, and uniting the world of mathematics to define the future of AI.
Felix Klein’s Erlangen Programme brought a revolutionary, unifying perspective to geometry and symmetry
Built on an active network established through previous influential EPSRC-funded projects, the hub was propelled by a foundation of collaborative research that had already positioned the UK as a world-leader in applied and computational topology. With a ‘dream team’ of experts spanning the UK’s leading academic institutions, the hub has forged close ties with major industry players, ensuring that its every step is defined by real world requirements.
Originally the brainchild of Professor Michael Bronstein at the University of Oxford, the hub’s management structure has been enhanced. Dr Anthea Monod of Imperial College London and Professor Jeffrey Giansiracusa of Durham University now sit alongside Bronstein as Co-Directors of the hub. The hub’s leadership team has collectively supervised more than 200 PhDs, received £117m in external funding, been awarded 4 Whitehead, 2 Adams, and 3 Leverhulme prizes, and created 17 tech spinout companies.
The hub’s leadership team (l-r, Prof Michael Bronstein, Dr Anthea Monod, and Prof Jeffrey Giansiracusa)
It is little wonder then that the hub’s first year alone has seen a raft of collaborative research both within and across the hub’s nodes, which span the length of the UK from Aberdeen to Southampton. The hub’s groundbreaking work has been presented at key forums and premier conferences in Machine Learning and AI, including the Neural Information Processing Systems conference (NeurIPS), the International Conference on Machine Learning (ICML), and the International Conference on Learning Representations (ICLR). It has also witnessed key collaborations across industry, government and beyond.
With the hub already allied with key industry partners, from the BBC and Ofcom to Siemens and Wm Morrison Supermarkets, new collaborations have emerged over the course of the first year. These include a collaboration with Microsoft Research, where topology was used to study the shape of LLM activations under adversarial influences, and a partnership with Oxford Drug Design, to improve virtual ligand screening in the drug development pipeline by leveraging geometric data analysis.
The hub’s first year also established major inroads into government, notably a partnership led by Professor Tom Coates and Dr Sara Veneziale at Imperial. Coates and Veneziale developed a training course entitled AI Fundamentals, which their team continues to deliver to civil servants across government, with bespoke versions being offered to AI-focused departments such as DSIT and the AI Security Institute. The collaboration brings an additional £1.2 million in funding, and three new PDRA positions hosted by the Imperial Policy Forum.
The growing ambition of the Erlangen AI Hub does not end there. A groundbreaking Taxonomy for AI Technologies, spearheaded by Professor Peter Grindrod at Oxford, is set to be rolled out. Built using simple language, the Taxonomy will act as a road map to help those in industry and beyond to better understand and incorporate AI technologies into their operations, and to help non-experts engage with the uses of AI in a more meaningful way.
“We believed it would only be a matter of time before the hub became a key player on the UK’s AI scene, but even so we are delighted by its impressive early impact. Mathematics is at the very core of AI, and AI is at the very heart of modern business and society. With our outstanding team, we are leveraging the power of mathematics to make a safer, more reliable AI future for us all.”
Hub Co-Director Professor Jeffery Giansiracusa
With the hub’s success predicated on the depth and breadth of its team, its early drive has been focused on growing its skills base. Overseen by academics from the University of Oxford, Durham University, Imperial College London, Queen Mary University of London, the University of Aberdeen, and the University of Southampton, the hub’s research is driven largely by its multi-talented Postdoctoral Research Associates (PDRAs) and PhD students.
In May, the hub gathered at the Maths Institute at Oxford to bring together its growing group of PDRAs and PhD students, to meet peers, share knowledge, and connect more closely with the mission of the hub. The event marked the conclusion of a highly formative first year for the hub and cemented its position as a growing, dynamic force, amassing some of the country’s finest minds working on cutting-edge research at the intersection of maths and AI.
The hub gathered at the Maths Institute in Oxford in May to bring together its growing group of researchers
The hub’s ambitious research programme applies geometry and topology to questions that underlie AI systems, via four themes of Understanding Data, Understanding ML Models, Understanding Learning, and Understanding Decision-Making. In May, PDRAs presented research in areas spanning Learning with Symmetries and Robust Verification of Stochastic Systems, to Non-Archimedean Optimisation and Topological Data Analysis on DNNs.
“We are very proud of our highly talented hub team, whose cutting-edge research at the crossover of maths and AI is breaking important new ground. Where maths once represented modern science, we are now leveraging its firm foundations to answer questions posed by the modern world of AI. It has been hugely satisfying to see the hub take shape and we are excited to see where it goes from here.”
Hub Co-Director Dr Anthea Monod
Following closely on the heels of the Oxford meet was the hub’s first ‘public launch’: a major three-day conference at Queen Mary University of London, which raised the hub to a new level. Over 100 leading minds gathered from across the UK’s mathematical, algorithmic and computational communities. It represented a seminal moment, uniting disparate academic fields and commercial stakeholders to advance the application of pure mathematics in AI.
Creating connections and forging a powerful coalition of experts – the hub’s first major conference at QMUL in June
In terms of attendance and high-quality scientific content, the event surpassed expectations. However, its lasting impact was that of creating connections and forging a powerful coalition of like-minded experts. True to the hub’s ethos, the conference helped bring composite knowledge into a single domain, stimulating debate, and ensuring that the concept of mathematics as the key to AI’s future was accessible to the widest possible audience.
As the hub’s industry partners play a major role in the life of the hub, so too did they make up a key element of the conference. With talks from high profile speakers from across industry, including Google DeepMind and Apple, and one of the conference’s three days dedicated to industry, the hub ensured that its focus stayed rooted in real world use cases, and that its world-leading research continues to be defined by and relevant to business and society.
As the Erlangen AI Hub’s team, expertise and partnerships continue to grow, so too does its reach and influence, and it can now rightly count itself a key part of the nation’s AI conversation. With a new website and newsletter to cater for its growing network, its future seems full of promise. However, just as it follows in the footsteps of the original Erlangen Programme, its transformative work is likely to reverberate well beyond its own lifetime.
The Erlangen AI Hub Conference took place on 9-11 June 2025 at Queen Mary University of London. It brought together over 100 leading minds from across the UK’s mathematical, algorithmic and computational communities to advance the application of pure mathematics in AI. It formed a key element of our exciting programme that aims to unite and revolutionise the mathematical field to unlock new and improved AI systems.
The conference featured a range of plenary and short talks from high profile speakers across academia and industry, including:
Relive the conference as we reported on it in real time below:
Day 1
There was a real buzz as we kicked off the conference at QMUL School of Mathematical Sciences, with an introduction from co-directors Michael Bronstein (Department of Computer Science, University of Oxford), Anthea Monod (Imperial College London), and Jeffrey Giansiracusa (Durham University Department of Mathematical Sciences), and a session from EPSRC’s Senior Portfolio Manager, AI & Robotics, Naomi South.
➕ Fascinating plenary talks
Our plenary speakers on day 1 were Kathlén Kohn of KTH Royal Institute of Technology, who spoke about Neuromanifolds, and UCL’s Benjamin Guedj who presented On Generalisation and Learning.
➕ Short talks
We also heard from Gesine Reinert of Department of Statistics, University of Oxford (Generating and Assessing Synthetic Networks), Imperial Postdoc Sara Veneziale (AI for Pure Mathematics), and Rik Sarkar of the The University of Edinburgh.
➕ Poster reception
The day concluded with a poster reception in the Maths Atrium, where successful poster submissions, judged by our panel, were presented to peers.
Day 2
Day 2 of the Erlangen AI Hub Conference was dedicated to industry.
Our industry partnerships and commercial links are central to our mission as we work to advance the expertise in and application of mathematics in AI across economy and society.
So, what did day 2 have in store?
➕ Plenary talks
Michael Bronstein (Department of Computer Science, University of Oxford) opened with a talk on Geometric Deep Learning: Quo Vadimus? Marco Cuturi of CREST – Center for Research in Economics and Statistics at ENSAE Paris / Apple later spoke about Optimal Transport and Generative Modeling.
➕ Industry talks
We also welcomed Darryl Hond of Thales to speak about The Challenge of Developing Trustworthy and Assured AI, and Richard Cooper of Oxford Drug Design outlined the Challenges and Opportunities for AI in Preclinical Drug Discovery.
➕ Industry panel
We were delighted to be joined by a stellar industry panel who facilitated a fascinating discussion and shared their perspectives and insights through the lens of various areas of industry. Our panel included Andreas Haggman of Ofcom, Danijela Horak of the BBC, Danica Vukadinović Greetham of Capgemini, and Andrew Paverd of the Microsoft Security Response Center.
➕ Taxonomy for AI Technologies
Tom Coates of Imperial College London spoke about a timely and important Taxonomy for AI Technologies, which is being spearheaded by Peter Grindrod CBE for the hub. Built using simple language, the Taxonomy aims to transform the way industry, government, strategists, the media and beyond understand and engage with AI. Tom’s talk was followed by a highly instructive workshopping session.
➕ Dinner
After a successful day, attendees came together to relax at a dinner in Queen Mary University of London’s stunning Queens’ Building, originally an educational and cultural venue in London known as the People’s Palace.
Day 3
We enjoyed the last of a fantastic three days at the Erlangen AI Hub Conference.
We were delighted to have brought together leading minds from across the globe, connecting diverse academic disciplines and institutions, and key industrial stakeholders, collaborating towards a common goal: to examine and transform AI through the powerful medium of mathematics.
We ended on a high with day 3 bringing more fascinating talks, insights and discussions:
➕ Plenary talks
We welcomed Arnaud Doucet of Google DeepMind to speak on Accelerated Denoising Diffusion Models via Speculative Sampling. Mark Sandler of Queen Mary University of London presented The Case for Artificial Neuroscience: Holistic Rigour for Understanding and Engineering Better Deep Learning. Lek-Heng Lim of University of Chicago visited us virtually to speak about Modern AI as the Compositional Approach to Function Approximation.
➕ Short talks
We also heard from Primoz Skraba of Queen Mary University of London (Approximating Metric Magnitude of Point Sets), Miguel Rodrigues of UCL (Safety Certification for Machine Learning Models under Adversarial Attacks), Jason Smith of Nottingham Trent University (Classifying Neural Stimuli on Biological Neural Networks), and Inés García-Redondo of Imperial College London (On the Limitations of Fractal Dimension as a Measure of Generalization).
We are grateful to all our speakers and attendees for joining us and making the conference such an enjoyable, informative, collaborative and inspiring event. We also thank QMUL School of Mathematical Sciences for being wonderful hosts. Here’s to the next one!
The Erlangen AI Hub kicked off its second year with an informative and enjoyable two-day event at the Mathematical Institute in Oxford.
The hub’s first year has flown by, and we were delighted to bring our growing team together for the Year 2 Kick Off event. We have been busy building our team of multi-talented Postdoctoral Research Associates (PDRAs) from across our partner institutions over the past year, and the event provided the perfect opportunity to get to know them and showcase their fascinating research.
Hub Co-Directors Michael Bronstein (Oxford) and Anthea Monod (Imperial) introduced the two-day event, before our PDRAs were given the floor to present a wide range of research projects at the intersection of Maths and AI. These included:
Edward Pearce-Crump (Imperial): Learning with Symmetries
Francesco Fabiano (Oxford): Thinking Fast and Slow in AI
Thom Badings (Oxford): Robust Verification of Stochastic Systems
Oliver Clarke (Durham): Non-Archimedean Optimisation
Eng-Jon Ong (QMUL): Topological Data Analysis on DNNs
Kate Zhu (Oxford): Beyond Second Order Methods for Nonconvex Optimisation with Applications to ML and AI
“I enjoyed attending the Year 2 Kick Off event. As a new postdoc who only joined in March, it was a fantastic opportunity to meet my new colleagues face to face for the first time, which was especially valuable given that the Hub is structured across six different nodes. I really enjoyed learning about their research and came away with a much clearer picture of the exciting projects and collaborations that we have planned for the year ahead.”
Edward Pearce-Crump, Postdoctoral Research Associate (Imperial)
The event also included a workshop highlighting the hub’s goals and its ways of working, led by Anthea Monod (Imperial) and Ran Levi (Aberdeen). Peter Grindrod CBE (Oxford) led a session about the importance of the hub’s industry stakeholders, emphasising the opportunities for working with our commercial partners. He also discussed the skills, leadership and career development opportunities available to our PRDAs through the hub’s research programme. The event closed with a highly informative Careers Panel organised by Yue Ren (Durham), where PDRAs were able to present a range of career-related questions to our Board of Directors.
“The Year 2 Kick Off was a great event full of inspiring talks and allowed me to get to know all of the others involved in the project.”
Thom Badings, Postdoctoral Research Associate (Oxford)
The Year 2 Kick Off was a highly successful and collaborative event, where team members old and new were able to get to know each other and exchange valuable knowledge and ideas in a professional, relaxed environment.
Many thanks to our attendees and we look forward to seeing you again soon!
Looking ahead
The collaborative spirit and knowledge-sharing on show at the Year 2 Kick Off gave a taste of things to come at our much-anticipated conference at Queen Mary University of London on 9-11 June. The conference promises to be a key component in our aims to unite and revolutionise the mathematical field to unlock new and improved AI systems. It will bring together leading minds from across the UK’s mathematical, algorithmic and computational communities, and will feature a range of high-profile speakers from across academia and industry.
