Past Events
April 2026 | |
| Thu 9 Apr 2026 14:00 - 15:00 | Seminar: Tom Berrett (Warwick): Density Ratio Permutation Tests with connections to distributional shifts and conditional two-sample testing Centre for Probability, Statistics and Data Science We introduce novel hypothesis tests to allow for statistical inference for density ratios. More precisely, we introduce the Density Ratio Permutation Test (DRPT) for testing $H_0: g \propto r f$ based on independent data drawn from distributions with... |
| Thu 2 Apr 2026 14:00 - 15:00 | Seminar: Rajen Shah (Cambridge): Hunt and test for assessing the fit of semiparametric regression models Centre for Probability, Statistics and Data Science We consider testing the goodness of fit of semiparametric regression models, such as generalised additive models, partially linear models, or quantile additive regression models. We propose an approach that involves first splitting the data in two... |
| Wed 1 Apr 2026 13:00 - 14:00 | Seminar: John Moriarty (QMUL): Branched harmonic majorants: representations for multidimensional optimal stopping Centre for Probability, Statistics and Data Science We give a constructive characterisation of the least superharmonic majorant arising in the optimal stopping problem for $d$-dimensional Brownian motion ($d\ge 2$) absorbed at the boundary of the unit ball, with continuous gain function $g$.... |
| Wed 1 Apr 2026 14:00 - 15:00 | Rainer Klages (QMUL): Modelling the movements of organisms: Movement ecology meets active particles and anomalous diffusion Centre for Probability, Statistics and Data Science Organisms living at very different spatio-temporal scales, from migrating in the microworld to foraging across the earth, display random-looking movement paths. Understanding these complex patterns by constructing mathematical models from data... |
March 2026 | |
| Thu 26 Mar 2026 14:00 - 15:00 | Seminar: Euan McGonigle (University of Southampton): General purpose time series segmentation using estimating functions Centre for Probability, Statistics and Data Science In time series analysis, many data sets of practical interest contain abrupt changes in structure, such as the canonical setting of change points in the mean. We propose new methodology based on estimating functions in a general framework for... |
| Wed 25 Mar 2026 14:00 - 15:00 | Seminar: Anuraag Bukkuri (City St George's University of London): Mathematical Models of Cancer Evolutionary Ecology and Cancer Social Science Centre for Probability, Statistics and Data Science The Bukkuri Lab develops and applies mathematical and philosophical methods to pose and address questions at the interface of cancer, evolutionary ecology, and social science. In this talk, I will focus on our cancer evolutionary ecology theme. I... |
| Thu 19 Mar 2026 | Seminar: Xiaowen Dong (Oxford): Bayesian optimisation of graph-based functions Centre for Probability, Statistics and Data Science The increasing availability of graph-structured data motivates a new type of optimisation problems over graph-based functions, i.e., searching for the graph or node that maximises the value of an underlying function. Such optimisation problems are... |
| Wed 18 Mar 2026 13:00 - 14:00 | Seminar: Codina Cotar (UCL): Some new results on non-convex random gradient Gibbs measures Centre for Probability, Statistics and Data Science In this talk we consider a class of gradient models with and without disorder. The simplest example of such models is the (lattice) Gaussian Free Field, which has quadratic potential V(s)=s^2/2. A well known result of Funaki and Spohn asserts that,... |
| Thu 12 Mar 2026 14:00 - 15:00 | Seminar: Yu Luo (KCL): General Bayesian updating using loss functions Centre for Probability, Statistics and Data Science In the usual Bayesian setting, a full probabilistic model is required to link the data and parameters, and the form of this model and the inference and prediction mechanisms are specified via de Finetti's representation. In general, such a... |
| Thu 5 Mar 2026 14:00 - 15:00 | Seminar: Helen Ogden (University of Southampton): Adaptively-Structured Mixed Models for Simple Clustered Data Centre for Probability, Statistics and Data Science I will describe a new class of flexible mixed-effects models for simple clustered or longitudinal data. The idea of these Adaptively-Structured Mixed Models (AdaStruMMs) is to replace pre-specified random-effects structure by unknowns to be... |
February 2026 | |
| Thu 26 Feb 2026 14:00 - 15:00 | Seminar: Chengchun Shi (LSE): Doubly Robust Alignment for Large Language Models Centre for Probability, Statistics and Data Science This talk focuses on reinforcement learning from human feedback (RLHF) for aligning large language models with human preferences. While RLHF has demonstrated promising results, many algorithms are highly sensitive to misspecifications in the... |
| Wed 25 Feb 2026 14:00 - 15:00 | Seminar: Thomas Wolley (Cardiff University): The Power of Noise Centre for Probability, Statistics and Data Science Turing patterns have found huge success as a mechanism for explaining patterns in biology, chemistry and phyiscs. However, one of the problems of applying Turing's theory to biology is the "Robustness Problem". Namely, small changes to the input... |
| Thu 19 Feb 2026 14:00 - 15:00 | Seminar: Edson Utazi (University of Southampton): Mapping the risk of Guinea worm disease in sub-Saharan Africa using geostatistical and machine learning approaches Centre for Probability, Statistics and Data Science High-resolution risk maps of infectious diseases such as Guinea worm disease (GWD, dracunculiasis) are crucial to guide the planning, implementation and monitoring of intervention strategies, including water treatment with Abate™ and surveillance... |
| Wed 18 Feb 2026 13:00 - 14:00 | Seminar: Pierre-François Rodriguez (ICL): Loop soups in 2 + epsilon dimensions Centre for Probability, Statistics and Data Science Abstract: the talk will be about a natural percolation model built from the so-called Brownian loop soup. We will give sense to studying it in dimension d = 2 + epsilon, with epsilon varying in [0,1], and discuss how to perform a rigorous "epsilon... |
| Wed 18 Feb 2026 14:00 - 15:00 | Seminar: Eleonora Secchi (ETH): Nonlinear rheology and mass transport in bacterial biofilms: a polymer-network perspective Centre for Probability, Statistics and Data Science Biofilms are aggregates of bacteria embedded in a self-secreted extracellular polymeric substance (EPS) matrix [1]. From a physical perspective, they can be regarded as living complex fluids [2]: soft, heterogeneous polymer networks that undergo... |
| Thu 12 Feb 2026 14:00 - 15:00 | Seminar: Dalia Chakrabarty (University of York): How Newton helps to forecast accurately Centre for Probability, Statistics and Data Science The state – i.e. "location" and "rate" – that a mechanistic system attains at a future time, is deterministically computable, given the state it is in now, since we know the potential function that causally connects any two states attained... |
| Wed 11 Feb 2026 13:00 - 14:00 | Seminar: Alexandre Stauffer (King's College London): Non-monotone phase transition in interacting particle systems Centre for Probability, Statistics and Data Science In this talk we will discuss a reaction-diffusion particle system which has a non-monotone phase transition. I will explain the techniques used to analyze monotone models and how they can be refined to analyze non-monotone particle systems.Based on... |
January 2026 | |
| Thu 29 Jan 2026 14:00 - 15:00 | Seminar: Rowland Seymour (Birmingham): Comparative Judgement Modeling to Map Forced Marriage at Local Levels Centre for Probability, Statistics and Data Science Forcing someone into marriage against their will is a violation of their human rights. In 2021, the county of Nottinghamshire, UK, launched a strategy to tackle forced marriage and violence against women and girls. We set out to map the risk of... |
| Thu 22 Jan 2026 14:00 - 15:00 | Seminar: Cristina Gualdani (QMUL): Robust identification in repeated games: An Empirical approach to algorithmic competition Centre for Probability, Statistics and Data Science We develop an econometric framework for recovering structural primitives—-such as marginal costs—-from price or quantity data generated by firms whose decisions are governed by reinforcement-learning algorithms. Guided by recent theory and... |
| Mon 12 - Tue 13 Jan 2026 |  Conference: Geometric Methods in ProbabilityCentre for Probability, Statistics and Data Science Monday 12th January will consist of a London Probability Day (LPD), a one-day conference in probability, with confirmed speakers: Annika Lang (Chalmers University of Technology and the University of Gothenburg) Iolo Jones (Durham University) Justin Salez (Université Paris-Dauphine & PSL) Tuesday 13th January will consist of a research workshop as part of the Tangents and New Normals (TnN) network. On this second day we will have motivational problems advertised by... |