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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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Juliane Mueller - Adaptive Computing and multi-fidelity learning - IPAM at UCLA

04 May 2023
49m
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Seshu Yamajala - Scaling NumPy applications from 1 CPU to thousands of GPUs - IPAM at UCLA

04 May 2023
36m
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Johannes Blaschke - ExaFEL: Achieving real-time XFEL data analysis using Exascale Hardware

04 May 2023
51m
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Johannes Köster - Transparent, reproducible, and adaptable data analysis with Snakemake

04 May 2023
38m
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Dilworth Dula Parkinson - X-ray micro-tomography at the Advanced Light Source & NERSC superfacility

04 May 2023
36m
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Michele Ceriotti - Machine learning for atomic-scale modeling - potentials and beyond - IPAM at UCLA

03 May 2023
50m
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Nestor Aguirre - Catalysis: Automated Multiscale Modeling and Active Exploration of Chemical Space

03 May 2023
39m
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Aurora Clark - high-dimension perspective on extracting & encoding information in chemical systems

03 May 2023
52m
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Ralf Drautz - From electrons to the simulation of materials - IPAM at UCLA

03 May 2023
56m
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Maxim Ziatdinov - From Human-Centric to AI-Driven Experimentation Workflows for Materials

03 May 2023
46m
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Joshua Schrier - Creating Complex Scientific Workflows that Reach into the Real World - IPAM at UCLA

03 May 2023
48m
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Marcus Noack - Gaussian Process Approximation & Uncertainty Quantification for Autonomous Experiment

02 May 2023
52m
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Alex Aiken - Task-Based Programming with Legion - IPAM at UCLA

02 May 2023
45m
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Claudia Draxl - High-throughput spectroscopy & material discovery by beyond-DFT work & data-analysis

02 May 2023
50m
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Jan Janssen - pyiron – Rapid-prototyping and Up-scaling Workflows for the Exascale - IPAM At UCLA

02 May 2023
52m
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Samuel Blau - High-Throughput DFT and Monte Carlo for Reaction Networks and Machine Learning

02 May 2023
50m
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Deborah Bard - The Superfacility Model for Connected Science - IPAM at UCLA

01 May 2023
51m
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Amedeo Perazzo - Workflows for experimental facilities and the digital twin approach - IPAM at UCLA

01 May 2023
40m
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Jörg Neugebauer - Enabling next-generation materials science simulations by automated workflows

01 May 2023
51m
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Genevieve Dusson - nonlinear reduced basis methods and transport in electronic structure calculation

01 May 2023
52m
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