Videos

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Michael Churchill - Using AI to accelerate fusion energy device design and operational excellence

May 7, 2026
IPAM

Matthew Landreman - Opportunities for multi-fidelity methods in fusion device design

May 7, 2026
IPAM

Hong Qin - Machine Learning of Local Confinement and Transport from the International Multi-Tokamak Confinement Profile Database

May 6, 2026
IPAM

Takeo Hoshi - General data-analysis framework ODAT-SE and its applications

May 5, 2026
IPAM

Cami Collins - Multi-Fidelity Integrated Modeling for Fusion Device Design with FREDA: From Workflows to Reliable Predictions

May 4, 2026
IPAM

Alexander Velberg - Data-driven discovery of sub-grid models for collisionless magnetic reconnection

April 18, 2026
IPAM

Benjamin Sanderse - Structure-preserving SciML for discovering ODEs and SDEs in fluid flows

April 17, 2026
IPAM

Boris Kramer - Structure-preserving Lift & Learn: Scientific machine learning for nonlinear conservative partial differential equations

April 17, 2026
IPAM

Leonardo Zepeda-Núñez - Learning Turbulent and Chaotic Dynamics via Data-Driven Probabilistic Models

April 16, 2026
IPAM
Tomo-Hiko Watanabe - Multi-scale turbulence and isotope effects on the trapped electron mode Thumbnail

Tomo-Hiko Watanabe - Multi-scale turbulence and isotope effects on the trapped electron mode

Presenter
  • Tomo-Hiko Watanabe
March 26, 2026
IPAM
Gabriele Merlo - Multi-fidelity approach to multiscale nature of plasma turbulence in stellarators Thumbnail

Gabriele Merlo - Multi-fidelity approach to multiscale nature of plasma turbulence in stellarators

Presenter
  • Gabriele Merlo
March 25, 2026
IPAM
Ben Zhu - A multi-fidelity approach in boundary plasma modeling - IPAM at UCLA Thumbnail

Ben Zhu - A multi-fidelity approach in boundary plasma modeling - IPAM at UCLA

Presenter
  • Ben Zhu
March 24, 2026
IPAM