Serge VaudenaySerge Vaudenay entered at the Ecole Normale Supérieure in 1989 with a major in mathematics. He earned his agrégation (secondary teaching degree) in mathematics in 1992, then a PhD in Computer Science at the University of Paris 7 - Denis Diderot in 1995. He subsequently became a senior research fellow at the CNRS, prior to being granted his habilitation à diriger des recherches (a postdoctoral degree authorizing the recipient to supervise doctoral students). In 1999, he was appointed as a Professor at the EPFL, where he created the Security and Cryptography Laboratory.
Marco MattavelliEnseignement et PhD A dirigé les thèses EPFL de Christophe Clerc, Ruohua Zhou, Beilu Shao, Christophe Lucarz, Richard Thavot, Ab Al Hadi Bin Ab Rahman, Endri Bezati, Simone Casale Brunet, Malgorzata Michalska, Ana Angelica Hernandez Lopez, Aurélien Bloch, Mustafa Besirli, Ünsal Öztürk A co-dirigé les thèses EPFL de Sylvain Aguirre Cours Systems and architectures for signal processing EE-555 Etude des composants essentiels eessentiels et des technologies des systèmes de traitements des signau
Pascal FrossardTeaching & PhD PhD Students Yiming Qin, Alba Carballo Castro, Elisa Messori, Ke Wang, Sevda Ögüt, Tuna Alikasifoglu, William Cappelletti, Manuel Madeira, Mahdi Amiri, Ortal Yona Senouf, Vasiliki Rizou, Cem Bilaloglu, Abdellah Rahmani, Amel Abdelraheem, Jérémy Jean Philippe Baffou, Adam Hazimeh, Vincent Jung, Yike Zhao Past EPFL PhD Students Dan Jurca, Jean-Paul Wagner, Ivana Radulovic, Ivana Tosic, Effrosyni Kokiopoulou, Zafer Arican, Vijayaraghavan Thirumalai, Tamara Tosic, Eirina Bourtsoulatze, Elif Vur
Michaël UnserExpertise
Image Processing Medical Imaging Biological Imaging Wavelets Splines Multiresolution
Enseignement et PhD Doctorant·es actuel·les Youssef Haouchat, Vincent Patrick Lawrence Guillemet, Bassam El Rawas, Stanislas Ducotterd, Mehrsa Pourya, Zhiyuan Hu A dirigé les thèses EPFL de Stefan Horbelt, Jan Kybic, Maria Arrate Munoz Barrutia, Manuela Feilner, Slavica Jonic, Mathews Jacob, Michael Liebling, Michael Sühling, Muthuvel Arigovindan, François Aguet, Cédric Vonesch, Ildar Khalidov, Sathish Ramani, F
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).
Rüdiger UrbankeRüdiger L. Urbanke obtained his Dipl. Ing. degree from the Vienna University of Technology, Austria in 1990 and the M.Sc. and PhD degrees in Electrical Engineering from Washington University in St. Louis, MO, in 1992 and 1995, respectively. He held a position at the Mathematics of Communications Department at Bell Labs from 1995 till 1999 before becoming a faculty member at the School of Computer & Communication Sciences (I&C) of EPFL. He is a member of the Information Processing Group. He is principally interested in the analysis and design of iterative coding schemes, which allow reliable transmission close to theoretical limits at low complexities. Such schemes are part of most modern communications standards, including wireless transmission, optical communication and hard disk storage. More broadly, his research focuses on the analysis of graphical models and the application of methods from statistical physics to problems in communications. From 2000-2004 he was an Associate Editor of the IEEE Transactions on Information Theory and he is currently on the board of the series "Foundations and Trends in Communications and Information Theory." In 2017 he was President of the Information Theory Society. From 2009 till 2012 he was the head of the I&C doctoral school, in 2013 he served as Dean a. i. of I&C, and since 2016 he is the Associated Dean for teaching of I&C. He is a co-author of the book "Modern Coding Theory" published by Cambridge University Press. Awards: 2021 IEEE Information Theory Society Paper Award 2016 STOC Best Paper Award 2014 La Polysphere Teaching Award 2014 IEEE Hamming Medal 2013 IEEE Information Theory Society Paper Award 2011 MASCO Best Paper Award 2011 IEEE Koji Kobayashi Award 2009 La Polysphere Teaching Award 2002 IEEE Information Theory Society Paper Award Fulbright Scholarship My students have won the following awards: M. Mondelli, 2021 IEEE Information Theory Paper Award M. Mondelli, EPFL Doctorate Award 2018 M. Mondelli, Patrick Denantes Award, 2017 M. Mondelli, IEEE IT Society Student Paper Award at ISIT, 2015 M. Mondelli, Dan David Prize Scholarship, 2015 H. Hassani, Inaugural Thomas Cover Dissertation Award, 2014 S. Kudekar, 2013 & 2021 IEEE Information Theory Paper Award A. Karbasi, Patrick Denantes Award, 2013 V. Venkatesan, Best Paper Award at MASCOTS, 2011 A. Karbasi, Best Student Paper Award at ICASSP, 2011 (with R. Parhizkar) A. Karbasi, Best Student Paper Award at ACM SIGMETRICS, 2010 (with S. Oh) S. Korada, ABB Dissertation Award, 2010 S. Korada, IEEE IT Society Student Paper Award at ISIT, 2009 (with E. Sasoglu) S. Korada, IEEE IT Society Student Paper Award at ISIT, 2008
Robert WestRobert West is a tenure-track assistant professor of computer science at EPFL, where he heads the Data Science Lab. In his research, he develops and applies techniques in machine learning, computational social science, natural language processing, social network analysis, and data mining. Bob also collaborates closely with the Wikimedia Foundation, in his role as a Wikimedia Research Fellow. Bob’s work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a best-paper runner-up award at WWW’16, a Google Faculty Research Award, a Facebook Research Award, a Hewlett-Packard Graduate Fellowship, and a Facebook Graduate Fellowship. He is actively involved in the research community, e.g., as an Associate Editor of ICWSM and EPJ Data Science and as a co-founder of the Wiki Workshop (held at WWW and ICWSM) and the Applied Machine Learning Days. Bob received his PhD in Computer Science from Stanford University, his MSc from McGill University, Canada, and his undergraduate degree from Technische Universität München, Germany.[Last updated: 25 Aug 2021]
Mohammad Amin ShokrollahiAmin Shokrollahi has worked on a variety of topics, including coding theory, computational number theory and algebra, and computational/algebraic complexity theory. He is best known for his work on iterative decoding algorithms of graph based codes, an area in which he holds a number of granted and pending patents. He is the co-inventor of Tornado codes, and the inventor of Raptor codes. His codes have been standardized and successfully deployed in practical areas dealing with data transmission over lossy networks.
Prior to joining EPFL, Amin Shokrollahi has held positions as the chief scientist of Digital Fountain, member of the technical staff at Bell Laboratories, senior researcher at the International Computer Science Insitute in Berkeley, and assistant professor at the department of computer science of the university of Bonn. He is a Fellow of the IEEE, and he was awarded the Best Paper Award of the IEEE IT Society in 2002 for his work on iterative decoding of LDPC code, the IEEE Eric Sumner Award in 2007 for the development of Fountain Codes, and the joint Communication Society/Information Theory Society best paper award of 2007 for his paper on Raptor Codes.
Auke IjspeertAuke Ijspeert is a full professor at the EPFL, and head of the Biorobotics Laboratory (BioRob). He has a B.Sc./M.Sc. in physics from the EPFL (1995), and a PhD in artificial intelligence from the University of Edinburgh (1999). He carried out postdocs at IDSIA and EPFL, and at the University of Southern California (USC). He then became a research assistant professor at USC, and an external collaborator at ATR (Advanced Telecommunications Research institute) in Japan. In 2002, he came back to the EPFL as an SNF assistant professor. He was promoted to associate professor in October 2009 and to full professor in April 2016. His primary affiliation is with the Institute of Bioengineering, and secondary affiliation with the Institute of Mechanical Engineering. His research interests are at the intersection between robotics, computational neuroscience, nonlinear dynamical systems, and machine learning. He is interested in using numerical simulations and robots to get a better understanding of sensorimotor coordination in animals, and in using inspiration from biology to design novel types of robots and adaptive controllers. (see for instance Ijspeert et al Science 2007, Ijspeert Science 2014, and Nyakatura et al Nature 2019). He is also investigating how to assist people with limited mobility using exoskeletons and assistive furniture. He is regularly invited to give talks on these topics (e.g. TED talk given at TED Global Geneva, Dec 8 2015). With his colleagues, he has received paper awards at ICRA2002, CLAWAR2005, IEEE Humanoids 2007, IEEE ROMAN 2014, CLAWAR 2015, SAB2018, and CLAWAR 2019. He is an IEEE Fellow, member of the Board of Reviewing Editors of Science magazine, and associate editor for the IEEE Transactions on Medical Robotics and Bionics and for the International Journal of Humanoid Robotics. He has acted as an associate editor for the IEEE Transactions on Robotics (2009-2013) and for Soft Robotics (2018-2021). He was a guest editor for the Proceedings of IEEE, IEEE Transactions on Biomedical Engineering, Autonomous Robots, IEEE Robotics and Automation Magazine, and Biological Cybernetics. He has been the organizer of 7 international conferences (BioADIT2004, SAB2004, AMAM2005, BioADIT2006, LATSIS2006, SSRR2016, AMAM2019), and a program committee member of over 50 conferences.
Pierre DillenbourgAncien instituteur primaire, Pierre Dillenbourg obtient un master en Sciences de lEducation (Université de Mons, Belgique). Dans son projet de master en 1986, il est l'un des premiers au monde à appliquer les méthodes de 'machine learning' à l'éducation, afin de développer un 'self-improving teaching system'. Ceci lui permettra de débuter une thèse de doctorat en informatique à l'Université de Lancaster (UK) dans le domaine des applications éducatives de lintelligence artificielle. Il a été Maître dEnseignement et de Recherche à lUniversité de Genève. Il rejoint l'EPFL en 2012, où Il fut le directeur du Centre de Recherche sur l'Apprentissage, la formation et ses technologies(CRAFT), puis académique du Centre pour l'Education à l'Ere Digitale (CEDE) qui met en oeuvre la stratégie MOOC de l'EPFL (plus de 2 millions d'inscriptions). Il est actuellement professeur ordinaire en technologies de formation aux sein de la faculté Informatique et Communications et dirige laboratoire d'ergonomie éducative (CHILI). Depuis 2006, il a aussi été le directeur de DUAL-T, la 'leading house' dédiée aux technologies pour les systèmes de formation professionnelle duale. Il a fondé plusieurs start-ups dans l'éducation et rejoint plusieurs conseils d'administration. En 2017, Il a créé avec des collègues le 'Swiss EdTech Collider', un incubateur qui rassemble 80 start-ups dans le domaine des technologies éducatives. En 2018, ils ont lancé LEARN, le centre EPFL pour les sciences de l'apprentissage, lequel regroupe les initiatives locales en innovation éducative. Pierre est un 'inaugural fellow of the International Society of Learning Sciences'. Il est actuellement le Vice-Président Associé pour l'Education à l'EPFL.
Friedrich EisenbrandEnseignement et PhD Doctorant·es actuel·les Ruben Manuel Skorupinski, Neta Singer, Lukas Vogl, Jiaye Wei A dirigé les thèses EPFL de Thomas Rothvoss, Nicolai Hähnle, Martin Niemeier, Adrian Aloysius Bock, Carsten Moldenhauer, Alfonso Bolívar Cevallos Manzano, Manuel Francesco Aprile, Igor Malinovic, Christoph Hunkenschröder, Moritz Andreas Venzin, Jana Tabea Cslovjecsek A co-dirigé les thèses EPFL de Puck van Gerwen Cours Algèbre linéaire avancée II - diagonalisation MATH-115(a) L'objectif
