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.

 

Fri, 04 Dec 2026

11:00 - 12:00
L4

To be announced

Dr Jochen Kursawe
(School of Mathematics and Statistics University of St Andrews)
Fri, 04 Dec 2026
12:00
Quillen Room N3.12

JART end of term social

Abstract

Junior Algebra & Representation Theory end of term social will happen in the Quillen Room at 12pm on Friday

Tue, 08 Dec 2026
11:00
L6

TBA

Lucas Benigni
(Université de Montréal)
Abstract

TBA

Tue, 08 Dec 2026
15:30

TBA

Yoav Len
(Mathematical Institute (University of St Andrews))
Thu, 10 Dec 2026

14:00 - 15:00
Rutherford Appleton Laboratory, nr Didcot

To be announced

Jose Roman
(Universitat Politècnica de València)
Abstract

TBA; hosted at RAL. 

Thu, 14 Jan 2027

14:00 - 15:00
(This talk is hosted by Rutherford Appleton Laboratory)

To be announced

Teresa Klatzer
(Lancaster University)
Abstract

TBA

Mon, 18 Jan 2027
14:15
L4

TBA

Riccardo Caniato
(Dept of Mathematics University of Warwick)
Tue, 19 Jan 2027
16:00
L5

TBC

Mikael Rørdam
(University of Copenhagen)
Abstract

to follow

Tue, 26 Jan 2027
16:00
L5

TBC

Jorge Garza Vargas
(MIT)
Abstract

to follow

Wed, 03 Feb 2027

17:00 - 18:30
L6

tbc

Erika Luciano
(Università degli Studi di Torino)
Abstract

tbc

Mon, 08 Feb 2027

14:00 - 15:00
Lecture Room 3

AI for Mathematics: open problems, a workflow, and what it leaves behind

Kate Wenqi Zhu
((Mathematical Institute University of Oxford))
Abstract

Kate Wenqi Zhu is a Postdoctoral Researcher at the Mathematical Institute, University of Oxford, who will give a talk on the topic of ‘AI for Mathematics: open problems, a workflow, and what it leaves behind’.

 

2026 has felt like a grokking moment for AI and mathematics. This talk is a working report from a numerical analyst, not an AI evangelist. I will describe (1) seven open problems from the numerical linear algebra catalogue that we resolved with AI agents, and how the community has responded; (2) the agent-to-agent workflow behind them, designed so that every proof is interpretable, traceable to its sources, and teachable, with independent cross-model review before anything is recorded as a result; (3) two worked examples: a deterministic eigenvalue-separation result whose proof pieces together convex analysis and classical numerical linear algebra, and a sum-of-squares result whose key idea we distilled into a reusable 'skill' for later problems; and (4) what I think this means for mathematicians: which problems suit AI, which suit people, and why asking the right question matters more than ever. I would like to leave time for an open discussion.

Thu, 18 Feb 2027

14:00 - 15:00
(This talk is hosted by Rutherford Appleton Laboratory)

TBA

Julian Hall
(University of Edinburgh)
Abstract

TBA

Tue, 23 Feb 2027
16:00
L5

TBC

Soham Chakraborty
(ENS)
Abstract

to follow

Thu, 25 Feb 2027

14:00 - 15:00
TBA

TBA

Rob Kirby
(Baylor University)
Abstract

TBA

Tue, 02 Mar 2027
16:00
L5

TBC

Maria Stella Adamo
(Kyoto University)
Abstract

to follow

Tue, 02 Mar 2027

17:00 - 18:30
L6

tbc

Raffaele Danna
(Sant’Anna School of Advanced Studies, Pisa)
Wed, 12 May 2027

17:00 - 18:30
tbc

tbc

Clare Moriarty
(University College Dublin/National Library of Ireland)
Thu, 20 May 2027

14:00 - 15:00
TBA

TBA

Ani Miraçi
(Laboratoire Jacques Louis Lions, Sorbonne Université)
Abstract

TBA

Mon, 07 Jun 2027

14:00 - 15:00
Lecture Room 3

To be announced

Professor Julie Delon
(École Normale Supérieure - PSL - Université Paris Cité)
Abstract

TBA