
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


Xiantao Li - A stochastic algorithm for self-consistent calculations in DFT - IPAM at UCLA

Gabor Csányi - Machine learning potentials: from polynomials to message passing networks

Ivan Oleynik - Materials at Extremes: Discovery Science with Exascale Computers and Experiment

Vasily Bulatov - What are we going to do with data generated in exascale simulations? - IPAM at UCLA

Daniel Schwen - MOOSE: Parallel sampling for rare event probabilities & inverse Bayesian inference

Steve Fitzgerald - Path integral formulation of stochastic processes... - IPAM at UCLA

Eric Cances - Error estimators for Density-Functional Theory - IPAM at UCLA

Laura Grigori - Randomization techniques for solving large scale linear algebra problems

Paul Kent - Extending the reach and accuracy of Quantum Monte Carlo in materials - IPAM at UCLA

Reinhold Schneider - Multi-Reference Coupled Cluster for Computation of Excited States & Tensors

Volker Blum - Large-scale electronic structure theory in FHI-aims and ELSI - IPAM at UCLA

Vikram Gavini - Fast, Accurate and Large-scale Ab-initio Calculations for Materials Modeling

David Bowler - Large-scale and linear scaling DFT: why we need it, and how we do it - IPAM at UCLA

Jaafar El-Awady - dislocation in high thermomechanical condition in Additive Manufacturing of Alloys

Virginie Ehrlacher - Sparse approximation of the Lieb functional in DFT with moment constraints

Manuel Athenes - Thermodynamic & transport properties of metal alloys: thermoelasticity & diffusion

Danny Perez - Scalable approaches to long-time atomistic dynamics: a journey to the exascale

Ramil Mouad - Parallel Replica algorithm for Langevin dynamics and Adaptative Metadynamics

Anders Nikklasson - Quantum-Mechanical Molecular Dynamics for Distributed Computing and AI-hardware
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