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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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Richard Sutton - The future of AI - IPAM at UCLA

12 Feb 2026
41m
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Terence Tao - Machine assistance and the future of research mathematics - IPAM at UCLA

12 Feb 2026
28m
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Barry Barish - LIGO: 10 Years of New Science - IPAM at UCLA

12 Feb 2026
24m
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Noah Brenowitz - Does progress in Earth System Modeling require more data, more compute, or both?

11 Feb 2026
37m
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David John Gagne - Physics and Uncertainty in the Community Research Earth Digital Intelligence Twin

06 Feb 2026
48m
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Franca Hoffmann - Efficient calibration for black-box physics-based models - IPAM at UCLA

06 Feb 2026
55m
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Haiwen Guan - LUCIE Lightweight Uncoupled Climate Emulator long-term stability, physical consistency

06 Feb 2026
53m
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Gary Froyland - Operator-theoretic methods for earth systems: atmosphere, ocean, and ML

06 Feb 2026
54m
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Claire Valva - Koopman operator methods for analysis of tropical climate variability - IPAM at UCLA

05 Feb 2026
47m
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Mohamed Iskandarani - Uncertainty Quantification in Ocean-Atmosphere Simulation w/ Polynomial Chaos

05 Feb 2026
47m
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Po-Lun Ma - Encoding microphysics in Earth system modeling with artificial intelligence

05 Feb 2026
49m
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Eduardo Siman - Image-to-Image Tropical Cyclone Wind Field Diagnosis - IPAM at UCLA

05 Feb 2026
53m
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Michael Fischer - Machine Learning Approach to Estimate 3-D Tropical Cyclone Kinematic Structure

05 Feb 2026
47m
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Maria Molina - Learning Without Labels: New Insights into Climate and Extremes - IPAM at UCLA

04 Feb 2026
59m
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Donifan Barahona - Synthesizing Observations, Simulations, & In Situ Data in Atmospheric Retrieval

04 Feb 2026
45m
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Milan Curcic - Deterministic AI Agents for Downstream Tasks & Application to Hurricane Forecasting

04 Feb 2026
52m
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Adam Rupe - A complex systems perspective on machine learning for Earth science - IPAM at UCLA

04 Feb 2026
40m
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Dimitris Giannakis - Operator-theoretic approach, feature extraction & statistical model of climate

03 Feb 2026
51m
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Damian Rouson - Cloud microphysics via progressive refinement mimicking maximal info entropy

03 Feb 2026
49m
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Tapio Schneider - Hybrid Physics/AI Model of Turbulence, Convection, & Cloud Feedback in CliMA Model

03 Feb 2026
47m
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