Karim AchouriEnseignement et PhD Doctorant·es actuel·les Mahmoud Abouelatta, Hossein Allahverdizadeh, Mustafa Yücel Cours Applied Electromagnetics for Metamaterial Design MICRO-449 This course provides the students with the appropriate electromagnetics foundation to understand, model and design metamaterials, especially two-dimensional electromagnetic and optical structures such as metasurfaces. This course covers concepts that apply to both the microwave and optical regimes. Ingénierie optique (pour
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
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.
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.
Patrick ThiranPatrick Thiran is a full professor in network and systems theory at the School of Computer and Communication Sciences at EPFL. He holds an electrical engineering degree from the Université Catholique de Louvain, Louvain-la-Neuve, Belgium, an M.Sc. degree in electrical engineering from the University of California at Berkeley, USA, and he received the PhD degree from EPFL, in 1996. He became an adjunct professor in 1998, an assistant professor in 2002, an associate professor in 2006 and a full professor in 2011. He was with Sprint Advanced Technology Labs in Burlingame, California, in 2000-01.
His research interests are in communication and social networks, performance analysis and stochastic models. He is currently active in the analysis and design of wireless and PLC networks (scaling laws, medium access control), in network monitoring (network tomography, multi-layer networks), and data-driven network science. He also contributed to network calculus and to the theory of locally coupled neural networks and self-organizing maps.
He served as an associate editor for the IEEE Transactions on Circuits and Systems in 1997-99 and for the IEEE/ACM Transactions on Networking in 2006-10. He is currently on the editorial board of the IEEE Journal on Selected Areas in Communication. He is/was on the program committee of different conferences in networking, including ACM Sigcomm, Sigmetrics, IMC, CoNext and IEEE Infocom. He was TPC chair of AMC IMC 2011 and CoNext 2012. He is a Fellow of the Belgian American Educational Foundation and of the IEEE. He received the 1996 EPFL Doctoral Prize and the 2008 Crédit Suisse Teaching Award.
Martin VetterliMartin Vetterli a été nommé Président de l'École polytechnique fédérale de Lausanne (EPFL) par le Conseil fédéral à l’issue d’un processus de sélection mené par le Conseil des EPF - qui l'a désigné à l'unanimité.
Né à Soleure le 4 octobre 1957, Martin Vetterli a suivi sa scolarité et effectué sa maturité dans le canton de Neuchâtel. Ingénieur en génie électrique de l’ETHZ (1981), diplômé de l’Université de Stanford (1982) et docteur en sciences de l’EPFL (1986), Martin Vetterli a enseigné à Columbia University comme professeur assistant puis associé. Il a ensuite été nommé professeur ordinaire au département du génie électrique et des sciences de l’informatique de l’Université de Berkeley, avant de revenir à l’EPFL en tant que professeur ordinaire à l’âge de 38 ans. Il a également enseigné à l’ETHZ et à l’Université de Stanford.
Ses activités de recherche centrées sur le génie électrique, les sciences de l’informatique et les mathématiques appliquées lui ont valu de nombreuses récompenses nationales et internationales, parmi lesquelles le Prix Latsis National, en 1996. Il est Fellow de l’Association for Computing Machinery et de l'Institute of Electrical and Electronics Engineers et membre de la National Academy of Engineering (NAE) notamment. Martin Vetterli a publié plus de 170 articles et trois ouvrages de référence.
Ses travaux sur la théorie des ondelettes, utilisées dans le traitement du signal, sont reconnus par ses pairs comme étant d’une portée majeure, et ses domaines de prédilection, comme la compression des images et vidéos ou les systèmes de communication auto-organisés, sont au cœur du développement des nouvelles technologies de l’information. En tant que directeur fondateur du Pôle de Recherche National Systèmes mobiles d’information et de communication, le professeur Vetterli est un fervent défenseur de la recherche transdisciplinaire.
Martin Vetterli connaît l’EPFL de l’intérieur. Alumnus de l’Ecole, il y enseigne depuis 1995, a été le vice-président chargé des relations internationales puis des affaires institutionnelles de l’Ecole entre 2004 à 2011, et doyen de la Faculté Informatique et Communication en 2011 et 2012. En parallèle à sa fonction de président du Conseil national de la recherche du Fonds national suisse qu’il a occupé de 2013 à 2016, il dirige le Laboratoire de Communications Audiovisuelles (LCAV) de l’EPFL depuis 1995.
Martin Vetterli a accompagné plus de 60 doctorants en Suisse et aux Etats-Unis pendant leur thèse et se fait un point d’honneur de suivre l’évolution de leur parcours au plus haut niveau, académique ou dans le monde entrepreneurial.
L’ingénieur est l’auteur d’une cinquantaine de brevets qui ont conduit à la création de plusieurs startups issues de son laboratoire, comme Dartfish ou Illusonic, ainsi qu’à des transferts de technologie par le biais de vente de brevets (Qualcomm). Il encourage activement les jeunes chercheurs à poursuivre ces efforts et commercialiser les résultats de leurs travaux.
Pierre VandergheynstPierre Vandergheynst received the M.S. degree in physics and the Ph.D. degree in mathematical physics from the Université catholique de Louvain, Louvain-la-Neuve, Belgium, in 1995 and 1998, respectively. From 1998 to 2001, he was a Postdoctoral Researcher with the Signal Processing Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. He was Assistant Professor at EPFL (2002-2007), where he is now a Full Professor of Electrical Engineering and, by courtesy, of Computer and Communication Sciences. As of 2015, Prof. Vandergheynst serves as EPFL’s Vice-Provost for Education. His research focuses on harmonic analysis, sparse approximations and mathematical data processing in general with applications covering signal, image and high dimensional data processing, computer vision, machine learning, data science and graph-based data processing. He was co-Editor-in-Chief of Signal Processing (2002-2006), Associate Editor of the IEEE Transactions on Signal Processing (2007-2011), the flagship journal of the signal processing community and currently serves as Associate Editor of Computer Vision and Image Understanding and SIAM Imaging Sciences. He has been on the Technical Committee of various conferences, serves on the steering committee of the SPARS workshop and was co-General Chairman of the EUSIPCO 2008 conference. Pierre Vandergheynst is the author or co-author of more than 70 journal papers, one monograph and several book chapters. He has received two IEEE best paper awards. Professor Vandergheynst is a laureate of the Apple 2007 ARTS award and of the 2009-2010 De Boelpaepe prize of the Royal Academy of Sciences of Belgium.
Johanni Michael BreaEnseignement et PhD Doctorant·es actuel·les Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Cours Biological data science II : machine learning BIO-322 Les étudiants comprennent les concepts et méthodes de base d'apprentissage automatique. Ils savent les décrire en termes mathématiques et ils savent les appliquer aux données en utilisant un langage de haut niveau (julia/python/R). Intelligence artificielle et société HUM-286 Ce cours intègre les SHS avec les sciences de l'
Wulfram GerstnerWulfram Gerstner is Director of the Laboratory of Computational Neuroscience LCN at the EPFL. His research in computational neuroscience concentrates on models of spiking neurons and spike-timing dependent plasticity, on the problem of neuronal coding in single neurons and populations, as well as on the link between biologically plausible learning rules and behavioral manifestations of learning. He teaches courses for Physicists, Computer Scientists, Mathematicians, and Life Scientists at the EPFL. After studies of Physics in Tübingen and at the Ludwig-Maximilians-University Munich (Master 1989), Wulfram Gerstner spent a year as a visiting researcher in Berkeley. He received his PhD in theoretical physics from the Technical University Munich in 1993 with a thesis on associative memory and dynamics in networks of spiking neurons. After short postdoctoral stays at Brandeis University and the Technical University of Munich, he joined the EPFL in 1996 as assistant professor. Promoted to Associate Professor with tenure in February 2001, he is since August 2006 a full professor with double appointment in the School of Computer and Communication Sciences and the School of Life Sciences. Wulfram Gerstner has been invited speaker at numerous international conferences and workshops. He has served on the editorial board of the Journal of Neuroscience, Network: Computation in Neural Systems', Journal of Computational Neuroscience', and `Science'.