Michael C. Gastpar
Full Professor
EPFL IC IINFCOM LINX
INR 130 (Bâtiment INR)
Station 14
CH-1015 Lausanne
+41 21 693 75 23
+41 21 693 64 59
Office:
INR 130
EPFL
>
IC
>
IINFCOM
>
LINX
Web site: Web site: https://linx.epfl.ch/
Data Analytics Group
c/o EPFL - AVP - SAO
CE 1 631 (Centre Est)
Station 1
CH-1015 Lausanne
Fields of expertise
Signal Processing
Communications
Systems Neuroscience
Biography
Michael Gastpar is a (full) Professor at EPFL. From 2003 to 2011, he was a professor at the University of California at Berkeley, earning his tenure in 2008.He received his Dipl. El.-Ing. degree from ETH Zürich, Switzerland, in 1997 and his MS degree from the University of Illinois at Urbana-Champaign, IL, USA, in 1999. He defended his doctoral thesis at EPFL on Santa Claus day, 2002. He was also a (full) Professor at Delft University of Technology, The Netherlands.
His research interests are in network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience.
He is a Fellow of the IEEE. He is the co-recipient of the 2013 Communications Society & Information Theory Society Joint Paper Award. He was an Information Theory Society Distinguished Lecturer (2009-2011). He won an ERC Starting Grant in 2010, an Okawa Foundation Research Grant in 2008, an NSF CAREER award in 2004, and the 2002 EPFL Best Thesis Award. He has served as an Associate Editor for Shannon Theory for the IEEE Transactions on Information Theory (2008-11), and as Technical Program Committee Co-Chair for the 2010 International Symposium on Information Theory, Austin, TX.
SUPPORT
We gratefully acknowledge support from:Publications
Selected publications
| E. Sula, M. Gastpar, and G. Kramer IEEE Transactions on Information Theory, 66(5):2860-2871, May 2020 |
Sum-Rate Capacity for Symmetric Gaussian Multiple Access Channels With Feedback |
| F. E. Rosas, P. Mediano, M. Gastpar, and J. Jensen Phys. Rev. E 100, 032305, 2019 |
Quantifying high-order interdependencies via multivariate extensions of the mutual information |
| B. Nazer and M. Gastpar IEEE Transactions on Information Theory, 57(10):6463-6486, October 2011. Received the 2013 Communications Society & Information Theory Society Joint Paper Award. |
Compute-and-Forward: Harnessing Interference Through Structured Codes |
| M. Gastpar IEEE Transactions on Information Theory, 53(2):471-487, February 2007 |
On capacity under receive and spatial spectrum-sharing constraints |
| G. Kramer, M. Gastpar, and P. Gupta IEEE Transactions on Information Theory, 51(9):3037-3063, September 2005 |
Cooperative strategies and capacity theorems for relay networks |
Teaching & PhD
Teaching
Communication Systems
Computer Science
PhD Programs
Doctoral program in computer and communication sciences
Doctoral Program in Neuroscience