Digital Twins

Mathematical and Statistical Foundations and Complex Applications

September 15 — December 12, 2025

Description

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A digital twin (DT) is a computational model of a physical system that continually updates its knowledge of the system by assimilating observational data to reduce uncertainties and improve predictions of the model, which in turn is used as a basis to inform decisions and optimally control the system to achieve a desired goal. The cycle of data assimilation and decision/control repeats over a continually evolving time horizon. Interest in DTs has intensified significantly in recent years in many areas of science, engineering, technology, health, finance, social systems, and beyond, driven by their potential to transform the role of models and data in decision-making for complex systems.

At the same time, DTs present significant mathematical, statistical, and computational challenges. This stems from the enormous complexity and scale of models describing many natural and engineered systems, the numerous uncertainties that underlie them, the complexity of observing systems and indirect and multimodal nature of the data they produce, the need to execute rapidly enough to support decisions and controls in time scales relevant to the physical system, and the critical societal impact of model-based decision making.

The long program will elucidate the mathematical, statistical, and computational challenges presented by DTs, explore avenues for overcoming them, and discuss state of the art applications to problems arising in complex systems in science, engineering, technology, medicine, and beyond. Events include an opening tutorial on data assimilation, three workshops on foundational components of DTs—data assimilation and inverse problems, optimal control and decision making under uncertainty, reduced order and surrogate models—and a final workshop integrating these components to address applications of digital twins in complex systems.

General Information on Long Programs

Long program participants spend time (generally, anywhere from a few days up to the full length of the program) in-person at IMSI with other researchers, creating new collaborations and generating new research in the program’s focus area. Participants who are only intending to apply for a workshop should not apply for the long program but should apply for the relevant workshop(s) instead. Long program participants can be PhD students, Postdocs, Faculty, or Researchers outside of academia such as national labs, industry, government, etc. There is some funding available, and funding can be requested in the application.

Organizers

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L C
Ludovic Chamoin Ecole Normale Supérieure Paris-Saclay
O G
Omar Ghattas The Oden Institute for Computational Engineering & Sciences, The University of Texas at Austin
Y M
Youssef Marzouk MIT
G S
Georg Stadler Courant Institute of Mathematical Sciences, New York University
K V
Karen Veroy-Grepl Technical University of Eindhoven

Program Workshops

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Application

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Applications received by January 10, 2025 will have the first priority for consideration.

In order to apply for this program, you must first have an IMSI account and be logged in. Please login or create an account, and then return to this page to apply for the program.