Rothschild Lecture: From Quantum Entanglement to Future Data-Driven Engineering

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• Robert Scheichl (Ruprecht-Karls-Universität Heidelberg)
• Wednesday 03 May 2023, 16:00-17:00
• Seminar Room 1, Newton Institute.

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DDE - The mathematical and statistical foundation of future data-driven engineering

In the last decade, parallel to the rise of data science and machine learning there has also been a vast growth in the interest and contributions from numerical analysis and scientific computing in high-dimensional Bayesian statistics, in order to efficiently combine data and physical models to better understand and control engineering problems with a quantitative measure of the remaining uncertainty. Simply opening the leading journals in the field or looking at recent job adverts will reveal this fact. But what are the problems and challenges that people are aiming to address, what are potential contributions and how can it benefit the field most effectively? In this talk, I will try to summarise some of the main areas of research where there are opportunities for numerical analysis to have an impact, but also the difficulties and barriers encountered. More specifically, I will present two exemplary approaches that use surrogates to significantly accelerate Bayesian computation in high-dimensional PDE -constrained applications: multilevel delayed acceptance MCMC [Lykkegaard et al, 2023], as well as a measure-transport approach based on low-rank tensor approximations [Cui et al, 2022].

This talk is part of the Isaac Newton Institute Seminar Series series.

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