Statistical Finite Element Methods - Mark Girolami (Cambridge, UK)

Title: Statistical Finite Element Methods

Speaker:  Mark Girolami (Sir Kirby Laing Professor of Civil Engineering at the University of Cambridge, UK, and Chief Scientist of the Alan Turing Institute, UK)

 

Abstract: The finite element method (FEM) is one of the great triumphs of applied mathematics, numerical analysis and software development. Recent developments in sensor and signalling technologies enable the phenomenological study of complex natural and physical systems. The connection between sensor data and FEM has been restricted to solving inverse problems placing unwarranted faith in the fidelity of the mathematical description of the system under study. If one concedes mis-specification between generative reality and the FEM then a framework to systematically characterise this uncertainty is required. This talk will present a statistical construction of the FEM which systematically blends mathematical description with data observations by endowing the Hilbert space of FEM solutions with the additional structure of a Probability Measure. 

 

Short Bio: Mark Girolami is the Sir Kirby Laing Professor of Civil Engineering within the Department of Engineering at the University of Cambridge where he also holds the Royal Academy of Engineering Research Chair in Data Centric Engineering. Prior to joining the University of Cambridge Professor Girolami held the Chair of Statistics in the Department of Mathematics at Imperial College London. He is the Chief Scientist of the Alan Turing Institute, which is the UK national institute for Data Science and AI. Professor Girolami is an elected fellow of the Royal Academy of Engineering and the Royal Society of Edinburgh, he was an EPSRC Advanced Research Fellow (2007-2012), an EPSRC Established Career Research Fellow (2012-2018), a recipient of a Royal Society Wolfson Research Merit Award, and in 2023 was awarded the Guy Medal in Silver by the Royal Statistical Society. He delivered the IMS Medallion Lecture at the Joint Statistical Meeting 2017, and the Bernoulli Society Forum Lecture at the European Meeting of Statisticians 2017.