"Uncertainty Quantification and Machine Learning Techniques Help Generating Digital Twins of Electronic Systems" - Flavio Canavero Ph.D.
Tuesday, October 30, 2018
1:30pm - 3:00pm
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Department of Electronics and Telecommunications
Politecnico di Tornio
This seminar modestly intends to illustrate some work of the research group lead by the presenter, aimed at a better understanding of the advantages and limitations of several simulation techniques w.r.t. the reliable replication of the behavior of electronic systems. The feasibility and strengths of the advocated methods are demonstrated based on benchmarks and on the statistical assessment of realistic structures employed in digital systems.
Bio Flavio G. Canavero received his electronic engineering Master degree from Politecnico (Technical University) of Torino, Italy, in 1977 and the Ph.D. degree from the School of Geophysical Sciences of Georgia Institute of Technology, Atlanta, USA, in 1986. He is currently a Professor of circuit theory with the Department of Electronics and Telecommunications, Politecnico di Torino. His research interests include signal integrity and EMC design issues, interconnect modeling, black-box characterization of digital integrated circuits, EMI and statistics for EMC. Dr. Canavero is an IEEE and URSI Fellow; he received several industrial and IEEE Awards, including the prestigious Richard R. Stoddard Award for Outstanding Performance, which is the EMC Society's highest technical award, and the Honored Member Award of the EMC Society. He has been the Editor-in-Chief for the IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY, the V.P. for Communication Services of the EMC Society, and the Chair of the URSI Commission E. Finally, Dr. Canavero has served in several positions (VP, Department Head, Dean of Graduate School…) within the Governing Bodies of his University.
Last revised October 22, 2018