Uploaded April 2026 | Updated September 2026, 3 weeks ago
Recorded 13 April 2026. Karen Willcox of the University of Texas at Austin presents "The Important Role of Mathematics in the Digital Twin Revolution" at IPAM's Learning Models from Data for Multi-Fidelity Fusion Plasma Physics Workshop.
Abstract: Digital twins represent the next frontier in the impact of computational science on grand challenges across science, technology and society. A digital twin is a computational model or set of coupled models that evolves over time to persistently represent the structure, behavior, and context of a unique physical system, process, or biological entity. Bidirectional interaction between the physical system and its virtual counterpart is central to the digital twin concept. This talk will highlight progress and open challenges in the mathematical foundations for achieving robust, reliable digital twins at scale, with illustrative examples of digital twins in engineering and medicine.
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-ii-learning-models-from-data-for-multi-fidelity-fusion-plasma-physics/
Recorded 13 April 2026. Karen Willcox of the University of Texas at Austin presents "The Important Role of Mathematics in the Digital Twin Revolution" at IPAM's Learning Models from Data for Multi-Fidelity Fusion Plasma Physics Workshop.
Abstract: Digital twins represent the next frontier in the impact of computational science on grand challenges across science, technology and society. A digital twin is a computational model or set of coupled models that evolves over time to persistently represent the structure, behavior, and context of a unique physical system, process, or biological entity. Bidirectional interaction between the physical system and its virtual counterpart is central to the digital twin concept. This talk will highlight progress and open challenges in the mathematical foundations for achieving robust, reliable digital twins at scale, with illustrative examples of digital twins in engineering and medicine.
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-ii-learning-models-from-data-for-multi-fidelity-fusion-plasma-physics/
