Please note that the list below only shows forthcoming events, which may not include regular events that have not yet been entered for the forthcoming term. Please see the past events page for a list of all seminar series that the department has on offer.

 

Thu, 06 Nov 2025

12:00 - 12:30
Lecture Room 4

TBA

Nian Shao
(École Polytechnique Fédérale de Lausanne - EPFL)
Abstract

TBA

Thu, 06 Nov 2025

14:00 - 15:00
Lecture Room 3

When AI Goes Awry

Des Higham
(University of Edinburgh)
Abstract

Over the last decade, adversarial attack algorithms have revealed instabilities in artificial intelligence (AI) tools. These algorithms raise issues regarding safety, reliability and interpretability; especially in high risk settings. Mathematics is at the heart of this landscape, with ideas from  numerical analysis, optimization, and high dimensional stochastic analysis playing key roles. From a practical perspective, there has been a war of escalation between those developing attack and defence strategies. At a more theoretical level, researchers have also studied bigger picture questions concerning the existence and computability of successful attacks. I will present examples of attack algorithms for neural networks in image classification, for transformer models in optical character recognition and for large language models. I will also show how recent generative diffusion models can be used adversarially. From a more theoretical perspective, I will outline recent results on the overarching question of whether, under reasonable assumptions, it is inevitable that AI tools will be vulnerable to attack.

Thu, 06 Nov 2025

16:00 - 17:00
L5

The value of information flows in the stock market - joint with Hai Duong

Prof. Bart Taub
(University of Glasgow)
Abstract
Stock market traders who trade because of information they possess reveal that information to the rest of the market in the process of bidding: if the information is positive they bid up the price, and if it is negative they lower it.   New information constantly develops and is brought to the market in this way, and because it influences prices, it ultimately influences the allocation of investments by firms.  
 
Using a new approach, we estimate the flow of this information and the price of that information (different from the stock price), and thus its value, for each stock, and then sum up this value across all stocks, obtaining an estimate of the total value of the dynamic flow of information in the stock market as a whole. This requires digesting the records of millions of stock orders (including cancelled orders, not just executed trades) to construct the dynamic limit order book and estimate the information flow and value from its structure.  
 
Our results support the notion that the cross-correlation of price impact across stocks is consistent with the CAPM: there is a single systematic component of price impact, and this is driven by the volatility of the systematic component of the stock market. This result suggests that by separating the underlying information into two components, systematic and idiosyncratic, informed traders distinguish between productive assets that have a systematic impact on the economy and those that can be diversified.  


 

Thu, 06 Nov 2025
17:00
L3

TBA

Vincenzo Mantova
(University of Leeds)
Abstract
TBA
Fri, 07 Nov 2025

11:00 - 12:00
L4

Programming cells using feedback control and whole-cell models

Prof Lucia Marucci
(Dept of Maths University of Bristol)
Abstract
The ability to program and design ad hoc cellular and biological processes offers exciting opportunities in basic research, in the biotechnology industry and in the clinic. Difficulties in engineering cellular phenotypes robust to changes and perturbations, as well as the lack of established tools to design biological functions across scales, still represent major roadblocks.  
 
In this talk I will start discussing our recent research that leverages feedback control to engineer robust cellular phenotypes. I will show results obtained using intracellular, external or multicellular controllers in both bacterial and mammalian cells, and new applications of cybergenetics methodologies we are currently exploring.  I will also mention a complementary approach aimed at rational and computer-aided cell design via whole-cell models (WCMs), which are mathematical models designed to capture the function of all genes and multiscale processes within a cell. The design of minimal bacterial genomes will be used as a proof-of-concept; I will also show how machine learning can support WCMs’ output interpretation and solve their computational burden challenge.  
Our tools and results should make the design and control of complex cellular phenotypes and laboratory engineering a step closer.
Fri, 07 Nov 2025

12:00 - 13:15
L3

TBA

Ilya Losev
(Mathematical Insitute, Oxford)
Mon, 10 Nov 2025

14:00 - 15:00
Lecture Room 3

Reinforcement learning, transfer learning, and diffusion models

Prof Xin Guo
(Berkeley, USA)
Abstract

Transfer learning is a machine learning technique that leverages knowledge acquired in one domain to improve learning in another, related task. It is a foundational method underlying the success of large language models (LLMs) such as GPT and BERT, which were initially trained for specific tasks. In this talk, I will demonstrate how reinforcement learning (RL), particularly continuous time RL, can benefit from incorporating transfer learning techniques, especially with respect to convergence analysis. I will also show how this analysis naturally yields a simple corollary concerning the stability of score-based generative diffusion models.

Based on joint work with Zijiu Lyu of UC Berkeley.

 

 

Mon, 10 Nov 2025
14:15
L4

On the diffeomorphism classification of a certain family of non-negatively curved 7-manifolds

Martin Kerin
(Durham University)
Abstract

A 2-connected, rational homotopy 7-sphere is classified up to diffeomorphism by three invariants: its (finite) 4th cohomology group, its q-invariant and its Eells-Kuiper invariant.  The q-invariant is a quadratic refinement of the linking form and determines the homeomorphism type, while the Eells-Kuiper invariant then pins down the diffeomorphism type.  In this talk, I will discuss the diffeomorphism classification of a certain family of non-negatively curved, 2-connected, rational homotopy 7-spheres, discovered by Sebastian Goette, Krishnan Shankar and myself, which contains, in particular, all $S^3$-bundles over $S^4$ and all exotic 7-spheres.

Tue, 11 Nov 2025
14:00
L6

On the Local Converse Theorem for Depth $\frac{1}{N}$ Supercuspidal Representations of $\text{GL}(2N, F)$.

David Luo
Abstract

In this talk, we use type theory to construct a family of depth $\frac{1}{N}$ minimax supercuspidal representations of $p$-adic $\text{GL}(2N, F)$ which we call \textit{middle supercuspidal representations}. These supercuspidals may be viewed as a natural generalization of simple supercuspidal representations, i.e. those supercuspidals of minimal positive depth. Via explicit computations of twisted gamma factors, we show that middle supercuspidal representations may be uniquely determined through twisting by quasi-characters of $F^{\times}$ and simple supercuspidal representations of $\text{GL}(N, F)$. Furthermore, we pose a conjecture which refines the local converse theorem for general supercuspidal representations of $\text{GL}(n, F)$.

Tue, 11 Nov 2025
16:00
C3

TBC

Ghazaleh Asghari
(University of Reading)
Abstract

to follow

Thu, 13 Nov 2025

12:00 - 12:30
Lecture Room 4

TBA

Michael Hardman
(University of Oxford Department of Physics)
Abstract

TBA

Thu, 13 Nov 2025

12:00 - 13:00
L3

 Tsunamis;  and how to protect against them

Prof. Herbert Huppert FRS
(University of Cambridge)

The join button will be published 30 minutes before the seminar starts (login required).

Further Information

 

Professor Herbert Eric Huppert FRS
University of Cambridge | University of New South Wales

Herbert Huppert (b. 1943, Sydney) is a British geophysicist renowned for his pioneering work applying fluid mechanics to the Earth sciences, with contributions spanning meteorology, oceanography, and geology. He has been Professor of Theoretical Geophysics and the Founding Director of the Institute of Theoretical Geophysics at the University of Cambridge since 1989, and a Fellow of King’s College, Cambridge, since 1970. He has held a part-time Professorship at the University of New South Wales since 1990.

Elected a Fellow of the Royal Society in 1987, Huppert has served on its Council and chaired influential working groups on bioterrorism and carbon capture and storage. His distinctions include the Arthur L. Day Prize and Lectureship from the US National Academy of Sciences (2005), the Bakerian Lecture (2011), and a Royal Medal (2020). He is also a Fellow of the American Geophysical Union, the American Physical Society, and the Academia Europaea.

Thu, 13 Nov 2025

14:00 - 15:00
Lecture Room 3

Fast Algorithms for Optimal Viscosities in Damped Mechanical Systems

Francoise Tisseur
(University of Manchester)
Abstract

Optimal damping consists of identifying a viscosity vector that maximizes the decay rate of a mechanical system's response. This can be rephrased as minimizing the trace of the solution of a Lyapunov equation whose coefficient matrix, representing the system dynamics, depends on the dampers' viscosities. The latter must be nonnegative for a physically meaningful solution, and the system must be asymptotically stable at the solution.

In this talk, we present conditions under which the system is never stable or may not be stable for certain values of the viscosity vector, and, in the latter case, discuss how to modify the constraints so as to guarantee stability. We show that the KKT conditions of our nonlinear optimization problem are equivalent to a viscosity-dependent nonlinear residual function that is equal to zero at an optimal viscosity vector. To minimize this residual function, we propose a Barzilai-Borwein residual minimization algorithm (BBRMA) and a spectral projection gradient algorithm (SPG). The efficiency of both algorithms relies on a fast computation of the gradient for BBRMA, and both the objective function and its gradient for SPG. By fully exploiting the low-rank structure of the problem, we show how to compute these in $O(n^2)$ operations, $n$ being the size of the mechanical system.

 

This is joint work with Qingna Li (Beijing Institute of Technology).

 

 

Thu, 13 Nov 2025
16:00
Lecture Room 4

TBA

Thomas Bloom
(Manchester)
Abstract

TBA

Fri, 14 Nov 2025

11:00 - 12:00
L4

Self-generated chemotaxis of heterogeneous cell populations

Dr Mehmet Can Uçar
(School of Mathematical and Physical Sciences University of Sheffield)
Abstract

Cell and tissue movement during development, immune response, and cancer invasion depends on chemical or mechanical guidance cues. In many systems, this guidance arises not from long-range, pre-patterned cues but from self-generated gradients locally shaped by cells. However, how heterogeneous cell mixtures coordinate their migration by self-generated gradients remains largely unexplored. In this talk, I will first summarize our recent discovery that immune cells steer their long-range migration using self-generated chemotactic cues (Alanko et al., 2023). I will then introduce a multi-component Keller-Segel model that describes migration and patterning strategies of heterogeneous cell populations (Ucar et al., 2025). Our model predicts that the relative chemotactic sensitivities of different cell populations determine the shape and speed of traveling density waves, while boundary conditions such as external cell and attractant reservoirs substantially influence the migration dynamics. We quantitatively corroborate these predictions with in vitro experiments on co-migrating immune cell mixtures. Interestingly, immune cell co-migration occurs near the optimal parameter regime predicted by theory for coupled and colocalized migration. Finally, I will discuss the role of mechanical interactions, revealing a non-trivial interplay between chemotactic and mechanical non-reciprocity in driving collective migration.
 

Fri, 14 Nov 2025

11:00 - 12:00
L1

How to make the most of your tutorials

Abstract

This session will look at how you can get the most out of your lectures and tutorials. We’ll talk about how to prepare effectively, make lectures more productive, and understand what tutors expect from you during tutorials. You’ll leave with practical tips to help you study more confidently and make your learning time count.


This session is likely to be most relevant for first-year undergraduates, but all are welcome.

Fri, 14 Nov 2025
12:00
N4.01

Mathematrix: Maths Isn't Neutral with Hana Ayoob

Hana Ayoob
(Mathematrix)
Abstract

Mathematicians often like to think of maths as objective. Science communicator Hana Ayoob joins us to discuss how the fact that humans do maths means that the ways maths is developed, used, and communicated are not neutral.

Mon, 17 Nov 2025

14:00 - 15:00
Lecture Room 3

Self-Supervised Machine Imaging

Prof Mike Davies
(University of Edinburgh)
Abstract

Modern deep learning methods provide the state-of-the-art in image reconstruction in most areas of computational imaging. However, such techniques are very data hungry and in a number of key imaging problems access to ground truth data is challenging if not impossible. This has led to the emergence of a range of self-supervised learning algorithms for imaging that attempt to learn to image without ground truth data. 

In this talk I will review some of the existing techniques and look at what is and might be possible in self-supervised imaging.

Mon, 17 Nov 2025
15:30
L5

On the congruence subgroup property for mapping class groups

Henry Wilton
(Cambridge University)
Abstract

I will relate two notorious open questions in low-dimensional topology.  The first asks whether every hyperbolic group is residually finite. The second, the congruence subgroup property, relates the finite-index subgroups of mapping class groups to the topology of the underlying surface. I will explain why, if every hyperbolic group is residually finite, then mapping class groups enjoy the congruence subgroup property. Time permitting, I may give some further applications to the question of whether hyperbolic 3-manifolds are determined by the finite quotients of their fundamental groups.

Mon, 17 Nov 2025
15:30
L3

--

Eyal NEUMANN
(Imperial College London)
Mon, 17 Nov 2025

16:30 - 17:30
L4

Existence and nonexistence for equations of fluctuating hydrodynamics

Prof Johannes Zimmer
( TU-Munich)
Abstract

Equations of fluctuating hydrodynamics, also called Dean-Kawasaki type equations, are stochastic PDEs describing the evolution of finitely many interacting particles which obey a Langevin equation. First, we give a mathematical derivation for such equations. The focus is on systems of interacting particles described by second order Langevin equations. For such systems,  the equations of fluctuating hydrodynamics are a stochastic variant of Vlasov-Fokker-Planck equations, where the noise is white in space and time, conservative and multiplicative. We show a dichotomy previously known for purely diffusive systems holds here as well: Solutions exist only for suitable atomic initial data, but provably not for any other initial data. The class of systems covered includes several models of active matter. We will also discuss regularisations, where existence results hold under weaker assumptions.