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AI-Fun with ELLIS Seminar | Luca Magri: Scientific machine learning for chaotic forecasting and real-time digital twinning

AI FUN & ELLIS
Dates:23 October 2024
Times:11:00 - 12:00
What is it:Seminar
Organiser:Faculty of Science and Engineering
Who is it for:University staff, External researchers, Alumni, Current University students
Speaker:Luca Magri
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  • AI Fundamentals Website
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  • In category "Seminar"
  • In group "(DF) Data Science and AI"
  • By Faculty of Science and Engineering

The Manchester Centre for AI Fundamentals and Manchester's ELLIS Unit are co-hosting a series of seminars featuring expert researchers working in the fundamentals of AI.

Scientific machine learning for chaotic forecasting and real-time digital twinning

The ability of fluid mechanics modelling to predict the evolution of a flow is enabled by physical principles and empirical approaches. Physical principles, for example conservation laws, are extrapolative (until the assumptions upon which they hinge break down): they provide predictions on phenomena that have not been observed. Human beings are excellent at extrapolating knowledge because we are excellent at finding physical principles. Empirical modelling provides correlation functions within data. Artificial intelligence and machine learning are excellent at empirical modelling. In this talk, the complementary capabilities of both approaches will be exploited to achieve adaptive modelling and optimization of nonlinear, unsteady and uncertain chaotic dynamical systems. The focus of the talk is on computational methodologies for noise filtering, optimal design and turbulence learning. We will review recent advancements in physics-constrained autoencoding, flow reconstruction, and chaotic forecasting on manifolds. The methodologies will be combined to create a down-to-earth real-time digital twin of a hydrogen-fuelled aeroengine.

Luca is a Professor in Scientific Machine Learning at Imperial College London. Luca is a Fellow and group leader under the Data-Centric Engineering Programme of The Alan Turing Institute. Prior to joining Imperial, Luca was a Lecturer at Cambridge University Engineering Department, Royal Academy of Engineering (RAEng) Research Fellow, and Fellow of Pembroke College. Prior to becoming a lecturer and RAEng Research Fellow at Cambridge, he was a postdoctoral Fellow at Stanford University Center for Turbulence Research. He obtained his PhD in Engineering at the University of Cambridge. His research is currently funded by ERC, UKRI, and EPSRC.

To attend online, please follow the registration link.

Speaker

Luca Magri

Role: Professor

Organisation: Imperial College London and Alan Turing Institute

  • https://magrilab.ae.ic.ac.uk/

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ai-fun@manchester.ac.uk

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