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Michael Gastpar is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he specializes in Information Theory, Signal Processing, and Communications. He previously served as a professor at the University of California, Berkeley, where he achieved tenure in 2008. Gastpar earned his Dipl. El.-Ing. degree from ETH Zürich in 1997 and completed his MS degree at the University of Illinois at Urbana-Champaign in 1999. He defended his doctoral thesis at EPFL in 2002. His research interests focus on network information theory, coding techniques, and their applications in sensor networks and neuroscience. He has received several prestigious awards, including the 2013 Communications Society & Information Theory Society Joint Paper Award and the 2004 NSF CAREER award. He served as an Associate Editor for Shannon Theory in the IEEE Transactions on Information Theory from 2008 to 2011 and has also chaired several technical committees. Gastpar is a Fellow of the IEEE and has secured significant funding for his research from organizations such as the European Research Council and the U.S. National Institutes of Health.
University of California at Berkeley • Berkeley, CA
Held a professorship and earned tenure.
EPFL • Lausanne, Switzerland
Currently serving as a full professor.
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