Disruption Group Research at the 2026 IPAM Fusion Energy Long Program

The Institute for Pure and Applied Mathematics (IPAM) at UCLA hosted the long program Multi-Fidelity Methods for Fusion Energy from March 9 to June 12, 2026. The program brought together mathematicians, physicists, computer scientists, and engineers to address the challenges and opportunities of multi-fidelity modeling in fusion energy research. The long program included four focused workshops covering multi-fidelity methods, data-driven models, device design and optimization, and control methods for fusion-relevant problems.

PSFC Data Science Division Head and Disruption Group Leader Dr. Cristina Rea served as a member of the organizing committee for the long program and as a committee member for Workshop IV, Multi-Fidelity Methods to Enable Robust Optimization and Real-Time Control of Fusion Processes. Disruption Group member Rishabh Datta participated in Workshop I: Multi-Fidelity Methods for Fusion Plasma Physics, while Qiyun Cheng participated in Workshop II: Learning Models from Data for Multi-Fidelity Fusion Plasma Physics.

As part of the technical program, Cristina delivered a talk titled “Data-driven learning for disruption prevention and performance optimization” in Workshop II. Her presentation discussed key research gaps for present and future grid-scale tokamak devices, demonstrated the use of experimental fusion data, and highlighted the challenges of applying data-driven methods to noisy experimental measurements. Cristina also presented recent work from the Disruption Group, including the development of new scaling laws and progress toward prediction-first real-time control. The talk provided a practical connection between mathematical/theoretical methods and real fusion applications. During Workshop IV, Cristina also participated in the poster session, presenting an overview of ongoing research activities across the Disruption Group.

The IPAM long program underscored the growing attention to multi-fidelity modeling and data-driven approaches in fusion energy research. Through discussions spanning theory, computation, experiment, and control, the program provided a valuable forum for connecting advanced mathematical methods with the practical needs of next-generation fusion devices.

Picture credits: IPAM