The ninety-fourth UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, January 22, 2026.
2–3 PM — Eleni Chatzi (ETH Zürich, Department of Civil, Environmental and Geomatic Engineering)
Dynamics, Inference, and Uncertainty: Foundations of AI-Enhanced Digital Twins
This talk examines the role of structural dynamics as a foundation for inference under uncertainty in AI-enhanced Digital Twins. Structural assets are highly individual, operate under variable environmental and operational conditions, and are only partially observable. In this context, dynamical signatures, extracted through structured inference schemes such as modal analysis, provide compact and physically interpretable representations through which uncertainty can be quantified, propagated, and reduced.
The talk discusses how physics-enhanced machine learning (PEML), together with structured representations and reduced-order models, enables potent yet efficient approximations that synergize with available data. By embedding physical constraints, governing equations, and dynamical structure into learning architectures, these models balance prior knowledge with data-driven adaptation, reducing epistemic uncertainty while remaining scalable under limited or evolving observations. Structured low-dimensional representations further support stable learning, efficient uncertainty propagation, and interpretable model updates.
By framing dynamics as the interface between physics and data within the context of inference, the talk highlights pathways toward uncertainty-aware, interpretable digital twins capable of supporting resilient decision-making of complex infrastructure systems.
References:
- Discussing the spectrum of physics-enhanced machine learning: a survey on structural mechanics applications, 2024 - github
- On the Consistent Classification and Treatment of Uncertainties in Structural Health Monitoring Applications, 2024
- Grammar-based Ordinary Differential Equation Discovery, 2025 - github
- Structured Kolmogorov-Arnold Neural ODEs for Interpretable Learning and Symbolic Discovery of Nonlinear Dynamics, 2025 - github
Joint work with the further members of the group of Structural Mechanics & Monitoring at ETH Zürich
Organizing committee: Pierre Barbillon (MIA-Paris), Julien Bect (L2S), Nicolas Bousquet (EDF R&D), Vincent Chabridon (EDF R&D), Amélie Fau (LMPS), Filippo Gatti (LMPS), Clément Gauchy (CEA), Bertrand Iooss (EDF R&D), Alexandre Janon (LMO), Sidonie Lefebvre (ONERA), Didier Lucor (LISN), Sébastien Petit (LNE), Emmanuel Vazquez (L2S), Xujia Zhu (L2S).
Coordinators: Sidonie Lefebvre (ONERA) & Xujia Zhu (L2S)
Practical details: the seminar will be held online using Microsoft Teams.
If you want to attend this seminar (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay group on Teams, simply send an email and you will be invited. Please specify which email address the invitation must be sent to (this has to be the address associated with your Teams account).
You will find the link to the seminar on the "General" UQSay channel on Teams, approximately 15 minutes before the beginning.
The technical side of things: you can use Teams either directly from your web browser or using the "fat client", which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.
