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Institute for Pure & Applied Mathematics (IPAM) · 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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Li Wang - Suppressing Plasma Instability Through Constrained Optimization - IPAM at UCLA

13 Apr 2026
38m
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Steve Cowley - Multi-scale Plasma Turbulence — the key to fusion power - IPAM at UCLA

13 Apr 2026
54m
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IPAM "Quantum Topology, Character Varieties and Low-Dimensional Geometry" Fall 2026 Program Overview

01 Apr 2026
25m
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Tomo-Hiko Watanabe - Multi-scale turbulence and isotope effects on the trapped electron mode

27 Mar 2026
43m
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Genia Vogman - Anomalous transport in pulsed power, continuum kinetic sim, reduced transport models

26 Mar 2026
45m
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Ammar Hakim - On Constructing Numerical Schemes for a Hierarchy of Fusion Plasma Problems

26 Mar 2026
47m
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Anirban Chaudhuri - Multifidelity surrogates and decision-making for digital twins - IPAM at UCLA

26 Mar 2026
48m
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Maximilian Ruth - A Statistical Magnetohydrodynamic Equilibrium Model - IPAM at UCLA

25 Mar 2026
45m
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Alex Gorodetsky - Generalized structural exploitation in multi-fidelity sampling and learning

25 Mar 2026
47m
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David Hatch - Bridging the pedestal gap: intermediate-fidelity models for pedestal transport

25 Mar 2026
46m
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Gabriele Merlo - Multi-fidelity approach to multiscale nature of plasma turbulence in stellarators

25 Mar 2026
36m
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Ben Zhu - A multi-fidelity approach in boundary plasma modeling - IPAM at UCLA

24 Mar 2026
49m
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Bryan Reuter - Enhancing Particle-Based Kinetic Methods Through Multifidelity Discretizations

24 Mar 2026
49m
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Kentaro Hara - Multi-fluid, high-order moment models for partially ionized plasmas - IPAM at UCLA

23 Mar 2026
50m
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Amanda Howard - Multifidelity, domain decomposition, stacking for training physics-informed networks

23 Mar 2026
43m
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Elizabeth Qian - Multifidelity control variates for supervised learning - IPAM at UCLA

23 Mar 2026
37m
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Victor Artigues - Plasma Turbulence in TensorFlow: Reduced Models and Optimization - IPAM at UCLA

23 Mar 2026
43m
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Andrew Christlieb - An introduction to Scientific Machine Learning - IPAM at UCLA

13 Mar 2026
59m
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Ionut-Gabriel Farcas - A tutorial on multi-fidelity methods for fusion energy research, Pt. 2/2

13 Mar 2026
1h 14m
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Ionut-Gabriel Farcas - A tutorial on multi-fidelity methods for fusion energy research, Pt. 1/2

13 Mar 2026
1h 15m
Page 7

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