Prof. Konstantinos (Costas) Sarris
The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto
10 King’s College Rd., Toronto, ON, M5S 3G4 Canada
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Costas Sarris received the Diploma in electrical and computer engineering from the National Technical University of Athens, Athens, Greece, in 1997, and the M.Sc. degree in applied mathematics and the Ph.D. degree in electrical engineering from the University of Michigan, Ann Arbor, MI, USA, both in 2002.

He is a Professor with the Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada. His research area is computational electromagnetics, with an emphasis on time-domain modeling, adaptive mesh refinement, enhanced stability, and higher order methods. He also works on physics-based wireless propagation models (with full-wave, asymptotic, and hybrid techniques), uncertainty quantification, and scientific machine learning.

Dr. Sarris was a recipient of the 2021 Premium Award for Best Paper in IET Microwaves, Antennas & Propagation, the IEEE MTT-S Outstanding Young Engineer Award in 2013 and an Early Researcher Award from the Ontario Government in 2007. He was the TPC Chair of the 2015 IEEE AP-S International Symposium on Antennas and Propagation and the CNC/USNC Joint Meeting, the 2019 and 2023 MTT-S Numerical Electromagnetics, Multiphysics and Optimization (NEMO) Conference, the TPC Vice-Chair of the 2012 IEEE MTT-S International Microwave Symposium, and the Chair of the MTT-S Technical Committee on Field Theory and Numerical Electromagnetics (2018–2020). Since 2019, he has been serving as the Editor-in-Chief of the IEEE JOURNAL ON MULTISCALE AND MULTIPHYSICS COMPUTATIONAL TECHNIQUES. He was a Guest Editor of the IEEE Microwave Magazine’s Special Issue on machine learning for microwave engineering (October 2021), and an Associate Editor of the IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES (2009–2013) and the IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS (2007–2009).

Prof. Sarris has received multiple teaching awards for his work on undergraduate electromagnetic courses, including the University of Toronto Faculty of Applied Science and Engineering Teaching Award in 2021.

Titles of talks:

• The transformative impact of machine learning enabled computational electromagnetics on the future of wireless (general audience)
• Scientific machine learning for electromagnetic field computations
• From propagation models to physics-based digital twins of emerging wireless communication systems
• Realistic propagation models for RIS-enabled communication channels
• Efficient FDTD-based modeling of finite periodic structures