In this episode, I’m joined by Nathan Kutz, Professor of applied mathematics, electrical engineering and physics at the University of Washington.
Nathan and I met a few months ago at the Prepare.AI conference in St. Louis where he gave a talk on “Machine Learning to Discover Physics and Engineering Principles.” Our conversation is laser-focused on his research into the use of machine learning to help discover the fundamental governing equations for physical and engineering systems from time series measurements. We explore the application of his work to self-tuning fiber-optic lasers as well as to biological systems and other complex multi-scale systems.
The notes for this show can be found at twimlai.com/talk/162.
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