
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


Dominique Unruh - The quantum random oracle model Part 1 of 2 - IPAM at UCLA

Chris Peikert - Post Quantum assumptions - IPAM at UCLA

Anne Broadbent - Information-Theoretic Quantum Cryptography Part 2 of 2 - IPAM at UCLA

Anne Broadbent - Information-Theoretic Quantum Cryptography Part 1 of 2 - IPAM at UCLA

Craig Costello - Post-quantum key exchange from supersingular isogenies- IPAM at UCLA

Fang Song - Introduction to quantum computing Part 3 of 3 - IPAM at UCLA

Fang Song - Introduction to quantum computing Part 2 of 3 - IPAM at UCLA

Fang Song - Introduction to quantum computing Part 1 of 3 - IPAM at UCLA

Jonathan Katz - Introduction to Cryptography Part 3 of 3 - IPAM at UCLA

Jonathan Katz - Introduction to Cryptography Part 2 of 3 - IPAM at UCLA

Jonathan Katz - Introduction to Cryptography Part 1 of 3 - IPAM at UCLA

Cynthia Dwork - Differential Privacy and the US Census - IPAM at UCLA

Cynthia Dwork - Fairness, Justice, and … Algorithms? - IPAM at UCLA

Salome Viljoen - What makes datafication (legally) wrongful? - IPAM at UCLA

Ari Waldman - A Perfect Storm of Discrimination - IPAM at UCLA

Patricia Williams - Who Counts? Sex and Gender Configurations of "Persons Capable of Pregnancy"

Aaron Roth - Individual Probability, Reference Class Problem, Model Multiplicity, Reconciling Belief

Marzyeh Ghassemi - Designing Machine Learning Processes for Equitable Health Care Systems

Emma Pierson - Using data science to shed light on understudied problems in women's health
Follow this podcast in Podwise
Sign in to get AI summaries, transcripts and mind maps for any episode, including new ones.
