
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


Seshu Yamajala - Scaling NumPy applications from 1 CPU to thousands of GPUs - IPAM at UCLA

Johannes Blaschke - ExaFEL: Achieving real-time XFEL data analysis using Exascale Hardware

Johannes Köster - Transparent, reproducible, and adaptable data analysis with Snakemake

Dilworth Dula Parkinson - X-ray micro-tomography at the Advanced Light Source & NERSC superfacility

Michele Ceriotti - Machine learning for atomic-scale modeling - potentials and beyond - IPAM at UCLA

Nestor Aguirre - Catalysis: Automated Multiscale Modeling and Active Exploration of Chemical Space

Aurora Clark - high-dimension perspective on extracting & encoding information in chemical systems

Ralf Drautz - From electrons to the simulation of materials - IPAM at UCLA

Maxim Ziatdinov - From Human-Centric to AI-Driven Experimentation Workflows for Materials

Joshua Schrier - Creating Complex Scientific Workflows that Reach into the Real World - IPAM at UCLA

Marcus Noack - Gaussian Process Approximation & Uncertainty Quantification for Autonomous Experiment

Alex Aiken - Task-Based Programming with Legion - IPAM at UCLA

Claudia Draxl - High-throughput spectroscopy & material discovery by beyond-DFT work & data-analysis

Jan Janssen - pyiron – Rapid-prototyping and Up-scaling Workflows for the Exascale - IPAM At UCLA

Samuel Blau - High-Throughput DFT and Monte Carlo for Reaction Networks and Machine Learning

Deborah Bard - The Superfacility Model for Connected Science - IPAM at UCLA

Amedeo Perazzo - Workflows for experimental facilities and the digital twin approach - IPAM at UCLA

Jörg Neugebauer - Enabling next-generation materials science simulations by automated workflows

Genevieve Dusson - nonlinear reduced basis methods and transport in electronic structure calculation
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