Prof. Bahman Gharesifard
Control Group, Department of Mathematics and Statistics
Tuesday 2019-10-22 16:00
IST-Seminar-Room V9.2.255 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen
I present some results related to stabilization and structural controllability of sparse bilinear control systems, where by “sparse” it is meant that the underlying matrices are restricted to belong to a vector subpage given by a zero pattern. The main objective of the talk, nevertheless, is to familiarize the students with some classical results on bilinear control systems.
Bahman Gharesifard is an Associate Professor with the Department of Mathematics and Statistics at Queen's University. He held postdoctoral positions with the Department of Mechanical and Aerospace Engineering at University of California, San Diego 2009-2012 and with the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign from 2012-2013. He held a visiting faculty position at the Institute for Systems Theory and Automatic Control at the University of Stuttgart in summer of 2016, and is a Humboldt research fellow at the same institute in 2019-2020. He obtained his Ph.D. in Mathematics from Queen's University in 2009. He received the 2019 CAIMS-PIMS Early Career Award, jointly awarded by the Canadian Applied and Industrial Math Society and the Pacific Institute for the Mathematical Sciences, a Humboldt research fellowship for experienced researchers from the Alexander von Humboldt Foundation in 2019, and an NSERC Discovery Accelerator Supplement in 2019. He was a finalist, as an advisor, for the Best Student Paper Award at the American Control Conference in 2017. He received the Engineering and Applied Science First Year Instructor Teaching Award in 2015 and 2017, and was shortlisted for a Frank Knox Award for Excellence in Teaching in 2014. He serves on the Conference Editorial Board of the IEEE Control Systems Society, and as an Associate editor for the IEEE Control System Letters. His research interests include systems and controls, distributed control, distributed optimization and learning, geometric control theory, social and economic networks, game theory, geometric mechanics, and applied Riemannian geometry.