Concept
Rényi entropy
Related people (27)
Michael Christoph Gastpar
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.
Jean-Louis Scartezzini
Director of EPFL Solar Energy and Building Physics Laboratory (1994-present); Founder & Director of ENAC Institute of Infrastructures, Resources and Environment (2002-2009); Founder & Director of EPFL Doctoral Program in Environment (2002-2009); Co-Director of EPFL Institute of Building Technology (1994-1997); Associate Professor of Building Physics at EPFL (1994-1997); Associate Professor of Building Physics at University of Geneva (1990-1997); Group Leader & Research Fellow at the EPFL Solar Energy Research Group (1981-1989); Research Fellow at the Applied Geophysics Institute of University of Lausanne (1980-1981).
Nicolas Macris
Nicolas Macris received the PhD degree in theoretical physics from EPFL and then pursued his scientific activity at the mathematics department of Rutgers University (NJ, USA). He then joined the Faculty of Basic Science of EPFL, working in the field of quantum statistical mechanics and mathematical aspects of the quantum Hall effect. Since 2005 he is with the Communication Theories Laboratory and Information Processing group of the School of Communication and Computer Science and currently works at the interface of statistical mechanics, information theory and error correcting codes, inference and learning theory. He held long-term visiting appointments and collaborations with the University College and the Institute of Advanced studies in Dublin, the Ecole Normale Supérieure de Lyon, the Centre de Physique Theorique Luminy Marseille, Paris XI Orsay, the ETH Zürich and more recently Los Alamos National Lab. CV and publication list.
Volkan Cevher
Volkan Cevher received the B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and the Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in Atlanta, GA in 2005. He was a Research Scientist with the University of Maryland, College Park from 2006-2007 and also with Rice University in Houston, TX, from 2008-2009. Currently, he is an Associate Professor at the Swiss Federal Institute of Technology Lausanne and a Faculty Fellow in the Electrical and Computer Engineering Department at Rice University. His research interests include machine learning, signal processing theory, optimization theory and methods, and information theory. Dr. Cevher is an ELLIS fellow and was the recipient of the Google Faculty Research award in 2018, the IEEE Signal Processing Society Best Paper Award in 2016, a Best Paper Award at CAMSAP in 2015, a Best Paper Award at SPARS in 2009, and an ERC CG in 2016 as well as an ERC StG in 2011.
Philippe Gillet
Philippe GILLET completed his undergraduate studies in Earth Science at Ecole normale supérieure de la rue dUlm (Paris). In 1983 he obtained a PhD in Geophysics at Université de Paris VII and joined Université de Rennes I as an assistant. Having obtained a State Doctorate in 1988, he became a Professor at this same university, which he left in 1992 to join Ecole normale supérieure de Lyon.
The first part of his research career was devoted to the formation of mountain ranges particularly of the Alps. In parallel, he developed experimental techniques (diamond anvil cells) to recreate the pressure and temperature prevailing deep inside planets in the lab. These experiments aim at understanding what materials make up the unreachable depths of planets in the solar system.
In 1997, Gillet started investigating extraterrestrial matter. He was involved in describing meteorites coming from Mars, the moon or planets which have disappeared today and explaining how these were expelled from their original plant by enormous shocks which propelled them to Earth. He also participated in the NASA Stardust program and contributed to identify comet grains collected from the tail of Comet Wild 2 and brought back to Earth. These grains represent the initial minerals in our solar system and were formed over 4.5 billion years ago. He has also worked on the following subjects:
Interactions between bacteria and minerals.
Solid to glass transition under pressure.
Experimental techniques: laser-heated diamond anvil cell, Raman spectroscopy, X-ray diffraction with synchrotron facilities, electron microscopy.
Philippe Gillet is also active in science and education management. He was the Director of the CNRS Institut National des Sciences de lUnivers (France), the President of the French synchrotron facility SOLEIL and of the French National Research Agency (2007), and the Director of Ecole normale supérieure de Lyon. Before joining EPFL he was the Chief of Staff of the French Minister of Higher Education and Research.
Selected publications:
Ferroir, T., L. Dubrovinsky, A. El Goresy, A. Simionovici, T. Nakamura, and P. Gillet (2010), Carbon polymorphism in shocked meteorites: Evidence for new natural ultrahard phases, Earth and Planetary Science Letters, 290(1-2), 150-154.
Barrat J.A., Bohn M., Gillet Ph., Yamaguchi A. (2009) Evidence for K-rich terranes on Vesta from impact spherules. Meteoritics & Planetary Science, 44, 359374.
Brownlee D, Tsou P, Aleon J, et al. (2006) Comet 81P/Wild 2 under a microscope. Science, 314, 1711-1716.
Beck P., Gillet Ph., El Goresy A., and Mostefaoui S. (2005) Timescales of shock processes in chondrites and Martian meteorites. Nature 435, 1071-1074.
Blase X., Gillet Ph., San Miguel A. and Mélinon P. (2004) Exceptional ideal strength of carbon clathrates. Phys. Rev. Lett. 92, 215505-215509.
Gillet Ph. (2002) Application of vibrational spectroscopy to geology. In Handbook of vibrational spectroscopy, Vol. 4 (ed. J. M. Chalmers and P. R. Griffiths), pp. 1-23. John Wiley & Sons.
Gillet Ph., Chen C., Dubrovinsky L., and El Goresy A. (2000) Natural NaAlSi3O8 -hollandite in the shocked Sixiangkou meteorite. Science 287, 1633-1636.
Jean-Philippe Thiran
Jean-Philippe Thiran was born in Namur, Belgium, in August 1970. He received the Electrical Engineering degree and the PhD degree from the Université catholique de Louvain (UCL), Louvain-la-Neuve, Belgium, in 1993 and 1997, respectively. From 1993 to 1997, he was the co-ordinator of the medical image analysis group of the Communications and Remote Sensing Laboratory at UCL, mainly working on medical image analysis. Dr Jean-Philippe Thiran joined the Signal Processing Institute (ITS) of the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in February 1998 as a senior lecturer. He was promoted to Assistant Professor in 2004, to Associate Professor in 2011 and is now a Full Professor since 2020. He also holds a 20% position at the Department of Radiology of the University of Lausanne (UNIL) and of the Lausanne University Hospital (CHUV) as Associate Professor ad personam. Dr Thiran's current scientific interests include
Computational medical imaging: acquisition, reconstruction and analysis of imaging data, with emphasis on regularized linear inverse problems (compressed sensing, convex optimization). Applications to medical imaging: diffusion MRI, ultrasound imaging, inverse planning in radiotherapy, etc.Computer vision & machine learning: image and video analysis, with application to facial expression recognition, eye tracking, lip reading, industrial inspection, medical image analysis, etc.