Uploaded January 2026 | Updated September 2026, 3 weeks ago
Large-scale optimization and machine learning shape modern data science, and Courtney Paquette, Ph.D., McGill University, studies how to design and analyze algorithms for large-scale optimization problems motivated by applications and data science. Paquette draws on probability, complexity theory, and convex and non-smooth optimization, and examines scaling limits of stochastic algorithms. Speaking with Saura Naderi, UC San Diego, Paquette describes an unconventional path from finance to pure mathematics and explains how persistence and comfort with uncertainty support long-term research. She highlights the challenge of building missing foundations while advancing through graduate training, and she connects that experience to the realities of doing original work. Paquette also reflects on rapid progress in machine learning and frames AI systems as tools that can be used thoughtfully. [2/2026] [Show ID: 41119]
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Science and technology continue to change our lives. University of California scientists are tackling the important questions like climate change, evolution, oceanography, neuroscience and the potential of stem cells.
UCTV is the broadcast and online media platform of the University of California, featuring programming from its ten campuses, three national labs and affiliated research institutions. UCTV explores a broad spectrum of subjects for a general audience, including science, health and medicine, public affairs, humanities, arts and music, business, education, and agriculture. Launched in January 2000, UCTV embraces the core missions of the University of California -- teaching, research, and public service – by providing quality, in-depth television far beyond the campus borders to inquisitive viewers around the world.
(https://www.uctv.tv)
Large-scale optimization and machine learning shape modern data science, and Courtney Paquette, Ph.D., McGill University, studies how to design and analyze algorithms for large-scale optimization problems motivated by applications and data science. Paquette draws on probability, complexity theory, and convex and non-smooth optimization, and examines scaling limits of stochastic algorithms. Speaking with Saura Naderi, UC San Diego, Paquette describes an unconventional path from finance to pure mathematics and explains how persistence and comfort with uncertainty support long-term research. She highlights the challenge of building missing foundations while advancing through graduate training, and she connects that experience to the realities of doing original work. Paquette also reflects on rapid progress in machine learning and frames AI systems as tools that can be used thoughtfully. [2/2026] [Show ID: 41119]
Donate to UCTV to support informative & inspiring programming:
uctv.tv/donate
More videos from: Science Like Me
(uctv.tv/data-science/science-like-me)
More from: Data Science Channel
(uctv.tv/data-science)
Explore More Science & Technology on UCTV
(uctv.tv/science)
Science and technology continue to change our lives. University of California scientists are tackling the important questions like climate change, evolution, oceanography, neuroscience and the potential of stem cells.
UCTV is the broadcast and online media platform of the University of California, featuring programming from its ten campuses, three national labs and affiliated research institutions. UCTV explores a broad spectrum of subjects for a general audience, including science, health and medicine, public affairs, humanities, arts and music, business, education, and agriculture. Launched in January 2000, UCTV embraces the core missions of the University of California -- teaching, research, and public service – by providing quality, in-depth television far beyond the campus borders to inquisitive viewers around the world.
(https://www.uctv.tv)
