A modelling assessment of the impact of control measures on highly pathogenic avian influenza transmission in poultry in Great Britain.
Davis, C
Hill, E
Jewell, C
Rysava, K
Thompson, R
Tildesley, M
PLoS computational biology
volume 22
issue 1
e1013874
(05 Jan 2026)
Supporting data for the paper "Neural networks for learning macroscopic chemotactic sensitivity from microscopic models"
Erban, R
Wed, 22 Oct 2025
16:00 -
17:00
L6
Introduction to group cohomology and a fixed point theorem
Shaked Bader
(Mathematical Institute University of Oxford)
Abstract
Most of the talk would be devoted to basic definitions and cute facts that are easy to prove with group cohomology. In the second part I'll state and prove a recent fixed point theorem which is joint work with Saar Bader, Uri Bader and Roman Sauer. Both parts of the talk should be followable to anyone who knows undergraduate level Algebraic Topology.
Wed, 15 Oct 2025
16:00 -
17:00
L6
Dehn Surgery and Knots
Misha Shmalian
((Mathematical Institute University of Oxford))
Abstract
Dehn surgery is a method of building three-dimensional manifolds that is ubiquitous throughout low-dimensional topology. I will give an introduction to Dehn surgery and discuss recent work with M. Kegel on the uniqueness of Dehn surgery descriptions of 3-manifolds. To do this, I will discuss the reason that Dehn surgery is so prominent - namely that it interacts very well with many structures, such as the geometry and gauge theory of 3-manifolds. (I will do my very best to assume very little background knowledge.)
Thu, 19 Feb 2026
16:00 -
17:00
L5
The Neutrinos of the Order Book: what do rejected orders tell us?
Prof. Sam Howison
((Mathematical Institute University of Oxford))
Abstract
Conventional data feeds from exchanges, even L3 feeds, generally only tell one what happened: accepted submissions of maker and taker orders, cancellations, and the evolution of the order book and the best bid and ask prices. However, by analyzing a dataset derived from the blockchain of the highly liquid cryptocurrency exchange Hyperliquid, we are able to see all messages (4.5 bn in our one-month sample), including rejections. Unexpectedly, almost 60% of message traffic is generated by submission and subsequent rejection of a single order type: post-only limit orders sent to the 'wrong' (aggressive) side of the book, for example a buy limit order at a price at or above the best ask. Such orders are automatically rejected on arrival except in the (rare) case that the price moves up while the order is in transit. Nearly 30% of message traffic relates to cancellations, leaving a small fraction for all other messages.
I shall describe this order flow in detail, then address the question of why message traffic is dominated by rejected submissions which, by their nature, do not influence the order book in any way at all, and are invisible to all traders except the submitter. We propose that the reason lies in a market-making strategy whose aim is to gain queue priority immediately after any price change, and I shall show how the evidence supports this hypothesis. I shall also discuss the risk/return characteristics of the strategy, and finally discuss its pivotal role in replenishing liquidity following a price move.
Joint work with Jakob Albers, Mihai Cucuringu and Alex Shestopaloff.
Thu, 22 Jan 2026
16:00 -
17:00
L5
Bayesian dynamic portfolio optimization with informative constraints
Jonathan Tam
((Mathematical Institute University of Oxford))
Abstract
There is a recent debate on whether sustainable investing necesarily impact portfolio performance negatively. We model the financial impact of portfolio constraints by attributing the performance of dynamic portfolios to contributions from individual constraints. We consider a mean-variance portfolio problem with unknown asset returns. Investors impose a dynamic constraint based on a firm characteristic that contains information about returns, such as the environmental, social, and governance (ESG) score. We characterize the optimal investment strategy through two stochastic Riccati equations. Using this framework, we demonstrate that, depending on the correlation between returns and firm characteristics, incorporating the constraint can, in certain cases, enhance portfolio performance compared to a passive benchmark that disregards the information embedded in these constraints. Our results shed light on the role of implicit information contained in constraints in determining the performance of a constrained portfolio.
This project is joint work with Ruixun Zhang (Peking University), Yufei Zhang (Imperial College London) and Xunyu Zhou (Columbia University).
Thu, 05 Mar 2026
16:00 -
17:00
L5
The Department of Psychiatry are looking for volunteers aged 18–65 who are experiencing low mood or reduced motivation to take part in a study testing a 7-day course of Losartan (a licensed blood pressure medicine) or placebo, and psychological training focused on activity scheduling.
Participants who complete the study will be reimbursed at least £140, plus reasonable travel expenses for visits.