Explore every episode of the podcast Numerical Optimization
| Title | Pub. Date | Duration | |
|---|---|---|---|
| Welcome to Numerical Optimization | 15 Nov 2024 | 00:01:00 | |
Our mission is to inspire the development of new math research aimed at solving real-world problems. We do this by sharing fun stories behind math formulas and the places they show up. | |||
| #1 — Stanley Osher | 25 Nov 2024 | 00:30:27 | |
Stanley Osher is a mathematician at University of California Los Angeles. Subscribe for updates and related optimization articles at Show Notes:
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| #2 — Deanna Needell | 29 Dec 2025 | 00:43:47 | |
Deanna Needell is a Professor of Mathematics at University of California, Los Angeles (UCLA) and a leading researcher in compressed sensing, numerical linear algebra, data science, and machine learning. Her work has shaped modern sparse recovery and randomized iterative algorithms, and she is widely known for co-developing CoSaMP, a cornerstone method in compressed sensing. More broadly, her research connects linear algebra and optimization with machine learning. Deanna’s research excellence has been recognized with several honors, including the IMA Prize in Mathematics and its Applications, an NSF CAREER Award, a Sloan Research Fellowship, and election as a Fellow of the American Mathematical Society and a Fellow of SIAM. Beyond theory, Deanna has applied mathematical tools to real-world problems in areas such as imaging, public health, and legal analytics, including work on Lyme disease data and collaborations with organizations like the California Innocence Project. She serves as the Executive Director for the Institute for Digital Research and Education and the Dunn Family Endowed Chair in Data Theory, and is deeply committed to mentorship, inclusiveness, and building bridges between mathematics and society. | |||