Events
FDS Special Seminar
Data-driven inference and physics-informed machine learning of active material models
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Speaker: Ivo F. Sbalzarini (TU Dresden) Professor of Computer Science, TU Dresden. Chair of Scientific Computing for Systems Biology, Center for Systems Biology Dresden (CSBD) Technische Universität Dresden Thursday, November 14, 2024 10:00AM - 11:00AM Location: Yale Institute for Foundations of Data Science, Kline Tower 13th Floor, Room 1327, New Haven, CT 06511 and via Webcast: https://yale.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=b3a26908-58d5-48df-a9d7-b21100eabccf |
“Data-driven inference and physics-informed machine learning of active material models”
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Speaker: Ivo F. Sbalzarini Group Leaderwww.mpi-cbg.de |
Abstract: Living materials, like cells and tissues, are mechanically active. They are able to move and deform by themselves, generating internal mechanical stresses by consuming a chemical fuel. Active material models describe the spatiotemporal dynamics of such non-equilibrium materials. They are key to understanding self-organization, e.g., in biological morphogenesis. Different descriptions of active materials exist, from interacting stochastic particles to mean-field partial differential equations. It is often unclear which description is sufficient to explain a given phenomenon, and many are hard to numerically solve or simulate. In this talk, I will show how stability-guided model selection enables noise-robust inference of minimal partial differential equation models of active materials from data with guaranteed physical consistency. I will also exploit the connection between numerical analysis and machine learning to remedy training pathologies in physics-informed neural networks for multi-scale active phenomena, such as active turbulence. These developments present exciting opportunities in applications from spatial biology, which are dominated by nonlinear processes in space and time with often unknown physics. This is showcased in our work on understanding biological tissue morphogenesis as a self-organized mechano-chemical process.
Speaker bio: Ivo Sbalzarini is a distinguished scientist specializing in computational biology, serving as a Senior Research Group Leader at the Max Planck Institute of Molecular Cell Biology and Genetics (MPI-CBG) in Dresden, Germany, and a Professor of Computer Science at TU Dresden. He is a founding member of the Center for Systems Biology Dresden (CSBD) and holds the Chair of Scientific Computing for Systems Biology at the Institute of Artificial Intelligence. With a career that spans institutions such as ETH Zurich, MedILS in Croatia, and ENS in Paris, Sbalzarini’s research focuses on data-driven and spatio-temporal modeling of biological processes, multi-scale simulations, and high-performance computing. He also founded the M.Sc. program in Computational Modeling and Simulation at TU Dresden and currently serves as Dean of the Faculty of Computer Science. His scientific achievements have earned him numerous honors, including teaching awards, best paper awards, and the prestigious Chorafas and Willi Studer Awards.
Hosted by Smita Krishnaswamy
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