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.
David Atienza AlonsoDavid Atienza Alonso is an associate professor of EE and director of the Embedded Systems Laboratory (ESL) at EPFL, Switzerland. He received his MSc and PhD degrees in computer science and engineering from UCM, Spain, and IMEC, Belgium, in 2001 and 2005, respectively. His research interests include system-level design methodologies for multi-processor system-on-chip (MPSoC) servers and edge AI architectures. Dr. Atienza has co-authored more than 350 papers, one book, and 12 patents in these previous areas. He has also received several recognitions and award, among them, the ICCAD 10-Year Retrospective Most Influential Paper Award in 2020, Design Automation Conference (DAC) Under-40 Innovators Award in 2018, the IEEE TCCPS Mid-Career Award in 2018, an ERC Consolidator Grant in 2016, the IEEE CEDA Early Career Award in 2013, the ACM SIGDA Outstanding New Faculty Award in 2012, and a Faculty Award from Sun Labs at Oracle in 2011. He has also earned two best paper awards at the VLSI-SoC 2009 and CST-HPCS 2012 conference, and five best paper award nominations at the DAC 2013, DATE 2013, WEHA-HPCS 2010, ICCAD 2006, and DAC 2004 conferences. He serves or has served as associate editor of IEEE Trans. on Computers (TC), IEEE Design & Test of Computers (D&T), IEEE Trans. on CAD (T-CAD), IEEE Transactions on Sustainable Computing (T-SUSC), and Elsevier Integration. He was the Technical Program Chair of DATE 2015 and General Chair of DATE 2017. He served as President of IEEE CEDA in the period 2018-2019 and was GOLD member of the Board of Governors of IEEE CASS from 2010 to 2012. He is a Distinguished Member of ACM and an IEEE Fellow.
Emmanuel AbbéMission
Chair of Mathematical Data Science (SB/IC)The research in the chair of Mathematical Data Science (MDS) focuses on the mathematical principles that underpin the analysis and design of information and data science technologies. As branches of mathematics, this involves probability, statistics, and discrete mathematics, and as specific fields, machine learning and information theory. Please consult http://deepfoundations.ai/ for postdoc applications.
Emmanuel Abbe received his Ph.D. degree from the EEC Alexandre Massoud AlahiAlexandre Alahi is currently an Assistant Professor at EPFL. He spent five years at Stanford University as a Post-doc and Research Scientist after obtaining his Ph.D. from EPFL. His research enables machines to perceive the world and make decisions in the context of transportation problems and smart environments. He has worked on the theoretical challenges and practical applications of socially-aware Artificial Intelligence, i.e., systems equipped with perception and social intelligence. He was awarded the Swiss NSF early and advanced researcher grants for his work on predicting human social behavior. He won the CVPR Open Source Award (2012) for his work on Retina-inspired image descriptors, and the ICDSC Challenge Prize (2009) for his sparsity-driven algorithm that has tracked more than 100 million pedestrians to date. His research has been covered internationally by BBC, abc, PBS, Euronews, Wall street journal, and other national news outlets around the world. Alexandre has also co-founded multiple startups such as Visiosafe, and won several startup competitions. He was elected as one of the Top 20 Swiss Venture leaders in 2010.
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
Alexander MathisAlexander studied pure mathematics with a minor in logic and theory of science at the Ludwig Maximilians University in Munich. For his PhD also at LMU, he worked on optimal coding approaches to elucidate the properties of grid cells. As a postdoctoral fellow with Prof. Venkatesh N. Murthy at Harvard University and Prof. Matthias Bethge at Tuebingen AI, he decided to study olfactory behaviors such as odor-guided navigation, social behaviors and the cocktail party problem in mice. During this time, he increasingly got interested sensorimotor behaviors beyond olfaction and started working on proprioception, motor adaption, as well as computer vision tools for measuring animal behavior.
In his group, he is interested in elucidating how the brain gives rise to adaptive behavior. One of the major goals is to synthesize large datasets into computationally useful information. For those purposes, he develops algorithms and systems to analyze animal behavior (e.g. DeepLabCut), neural data, as well as creates experimentally testable computational models.
Jean-Marc OdobezEnseignement et PhD Doctorant·es actuel·les Vivek Samir Gupte, Yesmine Abdennadher, Samy Tafasca, Shalutha Navindu Rajapakshe Rajapakshe Mudiyanselage, Gökhan Özbulak, Karl El Hajal, Hasindri Sankalpana Watawana, Mingchi Hou, Pierre François Marie Vuillecard, João Pedro Gandarela de Souza, Anirban Mukherjee, Elija Maria Vida, Nawal Haidar, Mojtaba Nafez A dirigé les thèses EPFL de Jagannadan Varadarajan, Alexandre Heili, Samira Sheikhi, Kenneth Alberto Funes Mora, Do Hoang Nam Le, Christian Jaques, Yu Yu,
Marcel SalathéEnseignement et PhD Doctorant·es actuel·les Laura Espinosa Montalbán, Marouane Toumi, Rohan Singh A dirigé les thèses EPFL de Gianrocco Lazzari, Martin Mathias Müller, Sharada Prasanna Mohanty Cours Digital epidemiology BIO-512 L'épidémiologie est fondamentale pour la médecine et la santé publique. Ce cours débute avec les principes clés de l'épidémiologie, avance vers les techniques de modélisation computationnelle, et finit avec les approches digitales. Les étudiants réaliseront un proto
Sébastien MarcelEnseignement et PhD Doctorant·es actuel·les Parsa Rahimi Noshanagh A co-dirigé les thèses EPFL de Fabien Cardinaux, Yann Rodriguez, Agnès Just, Guillaume Heusch, Anindya Roy, Venkatesh Bala Subburaman, Cosmin Atanasoaei, Laurent El Shafey, Ivana Chingovska, Tiago De Freitas Pereira, Amir Mohammadi, Alexander Unnervik, Hatef Otroshi Shahreza
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.
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'.
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
Berend SmitEnseignement et PhD Doctorant·es actuel·les Anastasia Blokhina, Raluca-Ana Kessler, Seyed Amirmohammad Elahi, Juliette Veronique Schleicher, Yutao Li, Xin Jin, Sara Bassetta, Beatriz Bueno Mouriño A dirigé les thèses EPFL de Samantha Lynn Anderson, Daniele Ongari, Andrzej Gladysiak, Seyedmohamad Moosavi, Arunraj Chidambaram, Bardiya Valizadeh, Stavroula Kampouri, Fatmah Ebrahim, Fatma Pelin Uran, Andres Adolfo Ortega Guerrero, Kevin Maik Jablonka, Elias Moubarak, Sauradeep Majumdar, Miriam Jasmin Pougin,
Antoine BosselutAntoine Bosselut is an assistant professor at EPFL. He leads the EPFL NLP group, which conducts research on natural language processing (NLP) systems that can model, represent, and reason about human and world knowledge.
Prior to joining EPFL, he was a postdoctoral researcher at Stanford University working in the
SNAP
and
NLP
groups and a young investigator on the
Mosaic
project at the
Allen Institute for AI
. He completed his PhD at the University of Washington.
