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Mike Giles elected Fellow of the Royal Society

Oxford Mathematician Mike Giles is a computational mathematician who has worked at the interface with both engineering and computer science. His early research was on computational fluid dynamics, developing algorithms and software which is today used by Rolls-Royce in the design of its aircraft engines. More recently, he moved into computational finance and more generally the area of Uncertainty Quantification, developing advanced Monte Carlo simulation methods
Optimal control of immune checkpoint inhibitor therapy in a heart-tumour model
 van der Vegt, S Baker, R Waters, S Bulletin of Mathematical Biology
Thu, 05 Jun 2025
16:00
Lecture Room 4

Refined conjectures of ‘Birch—Swinnerton-Dyer type’ and the theory of Euler systems

Dominik Bullach
(University College London)
Abstract

In the 1980s, Mazur and Tate proposed refinements of the Birch–Swinnerton-Dyer conjecture that also capture congruences between twists of Hasse–Weil L-series by Dirichlet characters. In this talk, I will report on new results towards these refined conjectures, obtained in joint work with Matthew Honnor. I will also outline how the results fit into a more general approach to refined conjectures on special values of L-series via an enhanced theory of Euler systems. This final part will touch upon joint work with David Burns.

Mike Giles elected Fellow of the Royal Society

Congratulations to Mike. He joins 31 other current and retired members of the department who are FRS.

Mike says, with the help of ChatGPT (humorous version): "Delighted to be elected a Fellow of the Royal Society. I plan to celebrate in the traditional scientific way: mild astonishment, followed by tea."

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Short stories

This week a neuroscientist and a mathematician talk about the challenges of collaboration. Here are Leo and Ramón.

Convergence and Near-optimal Sampling for Multivariate Function Approximations in Irregular Domains via Vandermonde with Arnoldi
 Zhu, W Nakatsukasa, Y IMA Journal of Numerical Analysis
Convergence and Near-optimal Sampling for Multivariate Function Approximations in Irregular Domains via Vandermonde with Arnoldi
 NAKATSUKASA, Y IMA Journal of Numerical Analysis
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