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Institute for Pure & Applied Mathematics (IPAM) ยท Science

Institute for Pure & Applied Mathematics (IPAM)

The Institute for Pure and Applied Mathematics (IPAM) is a National Science Foundation Math Institute at the University of California, Los Angeles (UCLA) that fosters the interaction of mathematics with a broad range of science and technology, builds new interdisciplinary research communities, promotes mathematical innovation, and engages and transforms the world through mathematics. IPAM fulfills its mission through workshops and programs that connect mathematics and other disciplines or multiple areas of mathematics. These activities bring in thousands of visitors annually from academia, government, and industry. The NSF has encouraged IPAM to make the scientific presentations of our speakers available to a wider audience. While this YouTube channel contains many of our most popular videos, our full video archive is available at www.ipam.ucla.edu/videos.

Episodes

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Brian Spears - The Genesis Mission: AI for US Science and Security Transformation - IPAM at UCLA

20 May 2026
32m
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Michael Abdelmalik - A Multi-Fidelity Framework for Rarefied Dynamics - IPAM at UCLA

19 May 2026
41m
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Jeff Schneider - Machine Learning for Scenario Design and Plasma Control in Tokamaks

19 May 2026
47m
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Bethany Lusch - Scalable graph-based surrogate models for unstructured meshes - IPAM at UCLA

18 May 2026
48m
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Pablo Rodriguez-Fernandez - Accelerate core plasma design/optimization w/ surrogate-assist transport

18 May 2026
42m
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Florian Schaefer - Information geometric regularization for sensitivities of flows with shocks

18 May 2026
45m
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Mark Kostuk - Mixed-Fidelity, Multi-Model Optimization within the DIII-D Digital Twin - IPAM at UCLA

18 May 2026
53m
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Syunichi Shiraiwa - Status of physics integration in radio-frequency H/CD modeling - IPAM at UCLA

08 May 2026
42m
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James Cook - Parametric Tokamak Design in BLUEMIRA - IPAM at UCLA

08 May 2026
40m
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Michael Churchill - Using AI to accelerate fusion energy device design and operational excellence

07 May 2026
47m
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Matthew Landreman - Opportunities for multi-fidelity methods in fusion device design - IPAM at UCLA

07 May 2026
51m
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Egemen Kolemen - Overview of AI4Fusion - IPAM at UCLA

07 May 2026
51m
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Lin Yang - Multi-scale & -physics Modeling Fusion Energy w/ MOOSE-Based Tools: TMAP8 and SALAMANDER

07 May 2026
46m
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Hong Qin - Machine Learning of Local Confinement & Transport from Int'l Multi-Tokamak Confinement DB

06 May 2026
33m
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Pablo Rodriguez-Fernandez - Designing tokamak core plasmas from scaling laws to first-principles sim

06 May 2026
40m
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Archis Joglekar - Differentiable, Multi-Fi Simulation for Integrated Inertial Fusion Energy Design

06 May 2026
32m
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Alan Kaptanoglu - Recent work on stage-1 and stage-2 stellarator optimization - IPAM at UCLA

05 May 2026
51m
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Yong-Su Na - Fusion Reactor Core Design: Historical DEMO, Power Plant Study, Design Methodology, Ops

05 May 2026
53m
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Takeo Hoshi - General data-analysis framework ODAT-SE and its applications - IPAM at UCLA

05 May 2026
45m
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Tim Slendebroek - From scaling laws to the design space: How we design machines we cannot yet build

04 May 2026
32m
Page 5

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