Contact InformationThe best way to reach me is via email: email@example.com
- May 3, 2021: I have decided to make my course notes for ME 4555 available to the public. This is an undergraduate course in classical control theory, and includes several interactive demos. I will continue to improve them over time.
- April 22, 2021: Akhil Sundararajan successfully defended his thesis! Congrats Akhil!
- Jan 8, 2021: Saman Cyrus successfully defended his thesis! Congrats Saman!
- Jan 6, 2021: New preprint on robust stabilization, with Saman Cyrus! See blog post and Twitter thread.
- Aug 24, 2020: Big news! I have moved to Northeastern University! I am now an Associate Professor in the Department of Mechanical & Industrial Engineering (with courtesy appointments in ECE and CS). I’m excited for this next chapter in my life and career here in Boston. Interested in joining my research group? Contact me!
Laurent Lessard is an Associate Professor of Mechanical and Industrial Engineering at Northeastern University, with courtesy appointments in ECE and CS. Before joining Northeastern, Laurent was a Charles Ringrose Assistant Professor of Electrical and Computer Engineering at the University of Wisconsin–Madison and a Faculty Member at the Wisconsin Institute for Discovery. Laurent received the B.A.Sc. in Engineering Science from the University of Toronto, and received the M.S. and Ph.D. in Aeronautics and Astronautics at Stanford University, advised by Sanjay Lall and co-advised by Matthew West. After completing his doctoral work, Laurent was an LCCC Postdoc at Lund University, Sweden, where he worked with Anders Rantzer. Subsequently, Laurent was a postdoctoral researcher at the University of California, Berkeley, where he worked in the Berkeley Center for Control and Identification with Andrew Packard and also collaborated with Ben Recht and others in the AMPLab. While at Berkeley, he was also partially supported by Kameshwar Poolla. Laurent is a recipient of the Hugo Schuck best paper award and the NSF CAREER award. His research interests include: decentralized control, robust control, optimization, and machine learning.
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