Michael Christoph GastparMichael 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.
Alireza KarimiAlireza Karimi received his B. Sc. and M. Sc. degrees in Electrical Engineering in 1987 and 1990, respectively, from Amir Kabir University (Tehran Polytechnic). Then he received his DEA and Ph. D. degrees both on Automatic Control from Institut National Polytechnique de Grenoble (INPG) in 1994 and 1997, respectively. He was Assistant Professor at Electrical Engineering Department of Sharif University of Technology in Teheran from 1998 to 2000. Then he joined Automatic Laboratory of Swiss Federal Institute of Technology at Lausanne, Switzerland. He is currently Professor of Automatic Control and the head of "Data-Driven Modelling and Control" group. His research interests include data-driven controller tuning and robust control with application to mechatronic systems and electrical grids.