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UID:6413cb3ee326b1884321fd535a4c8898-393
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DESCRIPTION:Models of Simplicity: Encounters in power systems, power electronics, and physiology
URL;VALUE=URI:https://www.csa.iisc.ac.in/newweb/event/393/models-of-simplicity-encounters-in-power-systems-power-electronics-and-physiology/
SUMMARY:Professor V.V.S. Sarma ("VVS") and his collaborators and students used, extended, and applied pattern recognition and machine learning/AI ideas and methods in a variety of areas, starting in the mid 1970's, but his interests expanded beyond: he wrote that "while my thoughts were on the philosophy of AI, my students were working on engineering aspects of AI and incorporation of AI ideas in system design." The VVS group's applications of AI in each domain - whether for speaker recognition, aircraft maintenance protocols, computer system reliability, hot forging processes in metallurgy, or remote sensing - were built on careful understanding of the application area (he refers to hours of "domain knowledge elicitation sessions"), to extract and exploit appropriate models for system design.  
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I began my academic career with a grounding similar to VVS's, in electrical engineering, and subsequently dynamic systems, control theory, and signal processing. Power systems and power electronics were my focus for 20+ years, but a sabbatical at a Boston hospital marked a switch to "computational physiology" for clinical inference. I seem to have landed in particular applications in these domains where the most elementary models have been disproportionately insightful and effective (with only tangential help from machine learning), and I will talk about these. 
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Biosketch:   George Verghese earned his BTech from IITM in '74, his MS from Stony Brook University in '75, and his PhD (under Prof. Thomas Kailath) from Stanford in '79, all in electrical engineering. He has been with the EECS Department at MIT ever since, where he is a chaired professor of electrical and biomedical engineering, and has won treasured MIT-wide awards for undergraduate education and for mentoring. He is an IEEE Fellow, and coauthor of Signals, Systems and Inference (2015, with Oppenheim) and Principles of Power Electronics (2nd edition, with Kassakian, Perreault and Schlecht, publication mid-2023, a mere 32 years after the 1st edition). 
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George Verghese earned his BTech from IITM in 74, his MS from Stony Brook University in 75, and his PhD (under Prof. Thomas Kailath) from Stanford in 79, all in electrical engineering. He has been with the EECS Department at MIT ever since, where he is a chaired professor of electrical and biomedical engineering, and has won treasured MIT-wide awards for undergraduate education and for mentoring. He is an IEEE Fellow, and coauthor of Signals, Systems and Inference (2015, with Oppenheim) and Principles of Power Electronics (2nd edition, with Kassakian, Perreault and Schlecht, publication mid-2023, a mere 32 years after the 1st edition). 
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