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Michael Gastpar is a full professor at École Polytechnique Fédérale de Lausanne (EPFL). He earned his Dipl. El.-Ing. degree from ETH Zürich in 1997 and completed his MS at the University of Illinois at Urbana-Champaign in 1999. He defended his doctoral thesis at EPFL in 2002. He has a rich academic history, having served as a professor at the University of California at Berkeley from 2003 to 2011, where he was awarded tenure in 2008. His research primarily focuses on network information theory, coding, signal processing techniques, and applications in sensor networks and neuroscience. Gastpar is a Fellow of the IEEE and has received numerous awards, including the Communications Society and Information Theory Society Joint Paper Award in 2013 and the ERC Starting Grant in 2010. He has also served as an Associate Editor for Shannon Theory in the IEEE Transactions on Information Theory and was the Technical Program Committee Co-Chair for the 2010 International Symposium on Information Theory in Austin, Texas.
École Polytechnique Fédérale de Lausanne • Lausanne, Switzerland
Full professor at EPFL specializing in information theory and signal processing.
University of California at Berkeley • Berkeley, CA, USA
Served as a professor and earned tenure.
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