- Michael Rabbat, Université McGill, Canada
Biographie : Michael G. Rabbat earned the B.Sc. from the University of Illinois at Urbana-Champaign in 2001, the M.Sc. from Rice University, in 2003, and the Ph.D. from the University of Wisconsin-Madison in 2006, all in electrical engineering. He joined McGill University, Montreal, QC, Canada, in 2007, and is currently an associate professor. He visited Télécom Bretagne and KTH Royal Institute of Technology during the 2013-2014 academic year, and he was a visiting researcher at Applied Signal Technology, Inc., during summer 2003. He conducts research at the intersection of statistical signal processing, networking, and machine learning. His current research focuses on distributed inference and optimization, and signal processing methods for data supported on graphs. Dr. Rabbat co-authored the paper which received the Best Paper Award (Signal Processing and Information Theory Track) at the 2010 International Conference on Distributed Computing in Sensor Systems (DCOSS). He received the Honorable Mention for Outstanding Student Paper Award at the 2006 Conference on Neural Information Processing Systems (NIPS) and a Best Student Paper Award at the 2004 ACM/IEEE International Symposium on Information Processing in Sensor Networks (IPSN). He received the 2013 McGill University Principal's Prize for Excellence in Teaching at the level of assistant professor. He is currently an Associate Editor for IEEE Signal Processing Letters and the new IEEE Transactions on Signal and Information Processing over Networks.