Applications of Optimization in Machine Learning and Engineering
Professor, Mechanical Engineering
25:23·2026·graduate level·Standalone Lecture
A high-level survey from the University of Washington on the diverse applications of optimization theory across modern machine learning, physics, and engineering disciplines.
Here we provide a high-level overview of some of the applications of optimization in modern machine learning, physics, and engineering. Applications include physics informed machine learning, control theory, inverse design, and the digital twin.
This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company.
Seminar notes & discussion
No public seminar notes on this lecture yet.