On August 11-15, 2025 there is the “Mathematical and Computational Foundations of Digital Twins” Workshop at CIRM, France.
This workshop will bring together experts from academia, industry, and research agencies to explore how advancements in real-time synchronization between digital twins and their physical counterparts, along with developments in areas such as surrogate modeling, control theory, inverse problems, large-scale Bayesian methods, reduced-order modeling, dimension reduction, data assimilation, and uncertainty quantification, can stimulate the advancement of digital twin technologies.
In addition to theoretical developments, the workshop will also feature discussions on real-world applications, highlighting how digital twin technologies are being applied across various domains including but not limited to industrial applications, various areas of Earth, life, and physical sciences, and mechanical, civil, and aerospace engineering.
The workshop aims to foster interdisciplinary collaboration and inspire new research in computational and applied mathematics that can meet the actual demands of complex, real-world applications, ensuring that digital twin technology is not only theoretically sound but also practically impactful.
The event will also provide young researchers with valuable insights into the relevance of this rapidly evolving field, guiding them in shaping their academic and industrial careers toward high impact areas in applied and computational mathematics.
Schedule
See Time schedule
Speakers
• Harbir Antil, George Mason University: Optimization and High Fidelity Digital Twins
• Théo Bourdais: Minimal Variance Model Aggregation: A principled, non-intrusive, and versatile integration of black box models
• Amy Braverman, Jet Propulsion Laboratory
• Tan Bui-Thanh, University of Texas At Austin: Towards Real-Time Probabilistic SciML algorithms for Digital Twins
• Matthieu Darcy: Kernel methods for operator learning
• Fariba Fahroo, Air Force Research Laboratory: Opening
• Charbel Farhat, Stanford University: An Adaptive Probabilistic Physics-Based Framework for High-Fidelity Digital Twins
• Roger Ghanem, University of Southern California: Recent Advances in Characterizing Model Error
• Omar Ghattas, University of Texas at Austin: Derivative informed neural operators (DINOs) for Bayesian inverse problems and optimal control under uncertainty
• David Ginsbourger, University of Bern: Modelling invariances and equivariances with GP models
• Alex Gorodetsky, University of Michigan: Towards understanding the effects of approximations in parameter-state data assimilation
• Maria Han Veiga, Ohio State University: Policy gradient algorithms for PDE based control problems
• Owhadi Houman (Caltech)
• Edgar Jaber, Edf R&D / Ens Paris-Saclay: A Bayesian methodology for hybrid degradation prognostics
• Alex Konomi, University of Cincinnati: Bayesian Multifidelity Transport Maps for Computer Models with Large non-Gaussian and non-linear Spatial Output
• Boris Kramer, University of California San Diego: Nonlinear control and balanced truncation for high-dimensional systems
• Christian Linder, Stanford University: Towards a digital twin for additive manufacturing
• Jodi Mead, Boise State University: Efficient Model Error Covariance Estimation in four dimensional variational data assimilation via the Representer Method and Regularization Techniques
• Sebastian Reich, University of Potsdam: Mean-field Pontryagin formulation for stochastic optimal control
• Nicolas Rouquette (et Propulsion Laboratory)
• Tuhin Sahai, Sri International: Automating the Discovery of Algorithms using Computational Language Processing
• Eric Savin, Centralesupélec: Generative diffusion for fluid flows
• Claudia Schillings, Freie University Berlin: Ensemble Kalman Methods for Optimization: Subspace Control, Subsampling, and Applications in Machine Learning and Optimal Control
• Jouni Susiluoto: Nasa Jet Propulsion Laboratory
• Daniel Tartakovsky, Stanford University: Reduced order models for digital twins
• Xin Tong: Diffusion models for high dimensional digital twins
• Dongbin Xiu, Ohio State University: Numerical Approach for Targeted Digital Twins: Direct Modelling of Quantity-of-Interest in Complex Simulation Models
• Guannan Zhang, Oak Ridge National Laboratory: Generative AI for Quantifying Uncertainties in Digital Twin Predictions using Observation Data
• Enrique Zuazua, University Of Erlangen-Nuremberg: HYCO: A Hybrid-Cooperative Strategy for Data-Driven PDE Model Learning
• Paolo Zunino, Polytechnic University of Milan: Probabilistic Formulation of Personalized Risk Assessment: A New Approach for Digital Twins in Oncology
WHEN
Mon.-Fri. August 11-15, 2025 at 09:00H (Berlin time)
WHERE
Auditorium A2. CIRM, International Centre Meetings Mathematics
163 avenue de Luminy, Case 916
13288 Marseille cedex 9, France
Organizing Committee
• Amy Braverman, Nasa Jet Propulsion Laboratory
• Fariba Fahroo, Air Force Office of Scientific Research
• Houman Owhadi, Caltech
• Jouni Susiluoto, NASA Jet Propulsion Laboratory
• Daniel M. Tartakovsky, Stanford University
• Dongbin Xiu, The Ohio State University
• Olivier Zahm, Inria, Université Grenoble Alpes
• Enrique Zuazua, FAU – Friedrich-Alexander-Universität Erlangen-Nürnberg
Participants
• Albert Alcalde, FAU – Friedrich-Alexander-Universität Erlangen-Nürnberg
• Harbir Antil, George Mason University
• Théo Bourdais, CALTECH
• Amy Braverman, Jet Propulsion Laboratory
• Tan Bui-Thanh, The University of Texas at Austin
• Wei Cai, Stanford university
• Pedro Luiz Coelho Rodrigues, Inria
• Matthieu Darcy, CALTECH
• Fariba Fahroo, Air Force Research Laboratory
• Charbel Farhat, Stanford University
• Roger Ghanem, University of Southern California
• Omar Ghattas, The University of Texas at Austin
• David Ginsbourger, University of Bern
• Yuliya Gorb, National Science Foundation
• Alex Gorodetsky, University of Michigan
• Heikki Haario, LUT University
• Maria Han Veiga, Ohio State University
• Sven Hirsch, Zurich University of Applied Sciences
• Owhadi Houman, CALTECH
• Edgar Jaber, EDF R&D / ENS Paris-Saclay
• Alex Konomi, University of Cincinnati
• Boris Kramer, University of California San Diego
• Rémi Lam, MIT
• Christian Linder, Stanford University
• Didier Lucor, CNRS CNRS, Université Paris-Saclay
• Jodi Mead, Boise State University
• Sebastian Reich, University of Potsdam
• Nicolas Rouquette, California Institute of Technology
• Tuhin Sahai, SRI International
• Éric Savin, Centrale Supélec
• Claudia Schillings, Freie University Berlin
• Jouni Susiluoto, NASA Jet Propulsion Laboratory
• Daniel Tartakovsky, Stanford University
• Xin Tong, National University of Singapore
• Dongbin Xiu, Ohio State University
• Olivier Zahm, INRIA Université Grenoble Alpes
• Guannan Zhang, Oak Ridge National Laboratory
• Enrique Zuazua, FAU – Friedrich-Alexander-Universität Erlangen-Nürnberg
• Paolo Zunino, Polytechnic University of Milano
_
See more at the official page of the event
