Paolo IennePaolo Ienne has been a Professor at the EPFL since 2000 and heads the Processor Architecture Laboratory (LAP). Prior to that, he worked for the Semiconductors Group of Siemens AG, Munich, Germany (which later became Infineon Technologies AG) where he was at the head of the Embedded Memories unit in the Design Libraries division. His research interests include various aspects of computer and processor architecture, FPGAs and reconfigurable computing, electronic design automation, and computer arithmetic. Ienne was a recipient of Best Paper Awards at the 20th, 24th, and 28th ACM/SIGDA International Symposia on Field-Programmable Gate Arrays (FPGA), in 2012, 2016 and 2020, at the 19th and 30th International Conference on Field-Programmable Logic and Applications (FPL), in 2009 and 2020, at the International Conference on Compilers, Architectures, and Synthesis for Embedded Systems (CASES), in 2007, and at the 40th Design Automation Conference (DAC), in 2003; many other papers have been candidates to Best Paper Awards in prestigious venues. He has served as general, programme, and topic chair of renown international conferences, including organizing in Lausanne the 26th International Conference on Field-Programmable Logic and Applications (FPL) in 2016. He serves on the steering committee of the IEEE Symposium on Computer Arithmetic (ARITH) and of the International Conference on Field-Programmable Logic and Applications (FPL). Ienne has guest edited a number of special issues and special sections on various topics for IEEE and ACM journals. He is regularly member of program committees of international workshops and conferences in the areas of design automation, computer architecture, embedded systems, compilers, FPGAs, and asynchronous design. He has been an associate editor of ACM Transactions on Architecture and Code Optimization (TACO), since 2015, of ACM Computing Surveys (CSUR), since 2014, and of ACM Transactions on Design Automation of Electronic Systems (TODAES) from 2011 to 2016.
Mark PaulyMark Pauly is a full professor at the School of Computer and Communication Sciences at EPFL. Prior to joining EPFL, he was assistant professor at the CS department of ETH Zurich since April 2005. From August 2003 to March 2005 he was a postdoctoral scholar at Stanford University, where he also held a position as visiting assistant professor during the summer of 2005. He received his Ph.D. degree (with distinction) in 2003 from ETH Zurich and his M.S. degree (with highest honors) in 1999 from TU Kaiserslautern. His research interests include computer graphics and animation, shape modeling and analysis, geometry processing, architectural geometry, and digital fabrication. He received the ETH medal for outstanding dissertation, was awarded the Eurographics Young Researcher Award in 2006 and the Eurographics Outstanding Technical Contributions Award in 2016.
Pascal FuaPascal Fua received an engineering degree from Ecole Polytechnique, Paris, in 1984 and the Ph.D. degree in Computer Science from the University of Orsay in 1989. He then worked at SRI International and INRIA Sophia-Antipolis as a Computer Scientist. He joined EPFL in 1996 where he is now a Professor in the School of Computer and Communication Science and heads the Computer Vision Laboratory. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and Augmented Reality. His research interests include shape modeling and motion recovery from images, analysis of microscopy images, and machine learning. He has (co)authored over 300 publications in refereed journals and conferences. He is an IEEE Fellow and has been an Associate Editor of IEEE journal Transactions for Pattern Analysis and Machine Intelligence. He often serves as program committee member, area chair, and program chair of major vision conferences and has cofounded three spinoff companies (Pix4D, PlayfulVision, and NeuralConcept).
Martin JaggiMartin Jaggi is a Tenure Track Assistant Professor at EPFL, heading the Machine Learning and Optimization Laboratory. Before that, he was a post-doctoral researcher at ETH Zurich, at the Simons Institute in Berkeley, and at École Polytechnique in Paris. He has earned his PhD in Machine Learning and Optimization from ETH Zurich in 2011, and a MSc in Mathematics also from ETH Zurich.
Roland SiegwartOriginaire d'Altdorf (UR) et d'Oberkirch (LU), Roland Siegwart est né en 1959 à Lausanne. Après une enfance à Schwyz, il a étudié à l'EPFZ et a obtenu son diplôme en génie mécanique en 1983. Il a travaillé ensuite comme assistant de recherche à l'EPFZ. En 1989, il a obtenu son doctorat, sa thèse traitant de l'application des paliers magnétiques sur les machines d'usinage de grande vitesse.
De 1989 à 1990, il a effectué des recherches à l'Université de Stanford en Californie (USA) et a participé à des projets en microrobotique. De retour en Suisse, il a rejoint l'Institut de robotique à l'EPFZ. Comme directeur remplaçant de l'Institut de Robotique, il a organisé les activités dans la micro- et nanorobotique. Il a mis notamment au pointuncourensystèmesélectroméca-niques appliqués.
Depuis 1990, R. Siegwart a été engagé en parallèle comme vice président de MECOS Traxler AG, une entreprise spin-off' de l'EPFZ. Il a dirigé de nombreux projets industriels dans le domaine des paliers magnétiques. ProfesseurauDépartementdemicrote-chnique de l'EPFL depuis 1996, R. Siegwart est responsable de la recherche en systèmes microtechniques autonomes. Le champ principal de ses activités porte sur les robots et les microrobots mobiles ainsi que les microsystèmes dynamiques et de très hautes performances.
Volkan CevherVolkan 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.
