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.
We'll discuss what mathematicians are looking for in written solutions. How can you set out your ideas clearly, and what are the standard mathematical conventions?
This session is likely to be most relevant for first-year undergraduates, but all are welcome.
Prof Ian Griffiths (a mental health first aider in the department) will lead a discussion about how to protect your mental health when studying an intense graduate degree and outline the support and resources available within the Mathematical Institute.
Quantum tomography involves obtaining a full classical description of a prepared quantum state from experimental results. We propose a Langevin sampler for quantum tomography, that relies on a new formulation of Bayesian quantum tomography exploiting the Burer-Monteiro factorization of Hermitian positive-semidefinite matrices. If the rank of the target density matrix is known, this formulation allows us to define a posterior distribution that is only supported on matrices whose rank is upper-bounded by the rank of the target density matrix. Conversely, if the target rank is unknown, any upper bound on the rank can be used by our algorithm, and the rank of the resulting posterior mean estimator is further reduced by the use of a low-rank promoting prior density. This prior density is a complex extension of the one proposed in [Annales de l’Institut Henri Poincaré Probability and Statistics, 56(2):1465–1483, 2020]. We derive a PAC-Bayesian bound on our proposed estimator that matches the best bounds available in the literature, and we show numerically that it leads to strong scalability improvements compared to existing techniques when the rank of the density matrix is known to be small.
Joint seminar organised by the Random Matrix Theory group. Note this seminar is on a TUESDAY.
TBA.
Come take a break and get to know other Mathematrix members over some crafts! All supplies and sweet treats provided.
The join button will be published 30 minutes before the seminar starts (login required).
Scott W. McCue is Professor of Applied Mathematics at Queensland University of Technology. His research spans interfacial dynamics, water waves, fluid mechanics, mathematical biology, and moving boundary problems. He is widely recognised for his contributions to modelling complex free-boundary phenomena, including thin-film rupture, Hele–Shaw flows, and biological invasion processes.
We apply techniques of exponential asymptotics to the KdV equation to derive the small-time behaviour for dispersive waves that propagate in one direction. The results demonstrate how the amplitude, wavelength and speed of these waves depend on the strength and location of complex-plane singularities of the initial condition. Using matched asymptotic expansions, we show how the small-time dynamics of complex singularities of the time-dependent solution are dictated by a Painlevé II problem with decreasing tritronquée solutions. We relate these dynamics to the solution on the real line.
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.
How do you efficiently look for jobs?
How can you make the most of careers fairs?
What makes a CV or cover letter stand out?
Get practical advice and bring your questions!
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 $\text{GL}(n, F)$.
The join button will be published 30 minutes before the seminar starts (login required).
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.
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.
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.
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.