
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


Andrea Bild - A Predictive, Biology-Driven Framework to Guide Cancer Therapy - IPAM at UCLA

Arne Traulsen - Evolutionary dynamics in Small Network Structured Populations - IPAM at UCLA

Michael Perlmutter - The Geometric Scattering Transform for High-dimensional Data Analysis

Samantha Riesenfeld - Quantum-Classical Algorithms for Biomarker Discovery in Multimodal Cancer Data

Andrew Blumberg - Manifold Learning and Optimal Transport in Genomics, Pt. 2/2 - IPAM at UCLA

Andrew Blumberg - Manifold Learning and Optimal Transport in Genomics, Pt. 1/2 - IPAM at UCLA

Konstantin Mischaikow - Dynamics of Regulatory Networks - IPAM at UCLA

Andrea Bertozzi - Machine Learning for High Throughput DNA-Aptamer Screening and Selection

Tuca Auffinger - Open Mathematical Problems in Manifold Learning for Single-Cell Data - IPAM at UCLA

Smita Krishnaswamy - Cellular Trajectories & Regulatory Networks w/ Neural & Graph ODE Models, 2/2

Smita Krishnaswamy - Cellular Trajectories & Regulatory Networks w/ Neural & Graph ODE Models, 1/2

Ingmar Glauche - Challenges in Modeling Hematopoietic Stem Cell Dynamics and Clonal Progression

Luis Aparicio - Random Matrix Theory Applications to Biology - IPAM at UCLA

Charles Epstein - The Kimura Diffusion Equation in Population Genetics, Theory and Numerics

Ben Raphael - Models and Algorithms for Cancer Evolution, Pt. 2/2 - IPAM at UCLA

Ben Raphael - Models and Algorithms for Cancer Evolution, Pt. 1/2 - IPAM at UCLA

Reinhard Laubenbacher - Mathematical Technology for Agent-Based Digital Twins - IPAM at UCLA

Eduardo Sontag - A Mathematical Model of Evolution of Drug-Induced Resistance - IPAM at UCLA

Herbert Levine - Cancer Drug Persistence; Modeling a Continuum of Phenotypic States - IPAM at UCLA
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