Regular biography
Michael Gastpar is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Department of Computer Science. His research interests include network information theory, coding, and signal processing techniques, with applications to sensor networks and neuroscience. He has held academic positions at the University of California at Berkeley and Delft University of Technology. Gastpar received his Dipl. El.-Ing. degree from ETH Zürich and his MS degree from the University of Illinois at Urbana-Champaign. He earned his doctoral thesis at EPFL in 2002. He is a Fellow of the IEEE and has received several awards, including the 2013 Communications Society & Information Theory Society Joint Paper Award. His work has also been recognized through an ERC Starting Grant and an NSF CAREER award.
Scholar-generated biography
Michael Gastpar is a professor at Ecole Polytechnique Fédérale (EPFL), Switzerland, specializing in Information Theory, Signal Processing, and Neuroscience. His research focuses on the theoretical and practical aspects of communication systems, including relay networks, interference management, and source-channel communication. He has contributed significantly to the understanding of cooperative strategies, network coding, and the capacity of wireless networks. His work also explores the intersection of information theory with neuroscience, particularly in the context of sensor networks and signal processing. Gastpar's publications often address fundamental questions in communication theory, such as the trade-offs between power, bandwidth, and distortion in large-scale systems.