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 HairerTeaching & PhD PhD Students Colin Piernot, Wenhao Zhao, Declan Rellan Stacy Courses Advanced stochastic analysis MATH-525 This course will give you in-depth knowledge in some topics of modern stochastic analysis. We will start with a general introduction to Gaussian measure theory followed by an introduction to Malliavin calculus and a selection of advanced topics.
Awards Fermat Prize Institut de Mathématiques de Toulouse 2013 Fields Medal IMU 2014 Honorary doctorate in science Hong Kong
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.
Max-Olivier HonglerExpertise
Processus stochastiquesContrôle optimal
Enseignement et PhD A dirigé les thèses EPFL de Yves Salama, Philippe Ciprut, Fabrice Dusonchet, Roger Filliger, Olivier Gallay, Julio Rodriguez, Guillaume Adrien Sartoretti
Yves PerriardYves Perriard was born in Lausanne in 1965. He received the M. Sc. in Microengineering from the Swiss Federal Institute of Technology - Lausanne (EPFL) in 1989 and the Ph D. degree in 1992. Co-founder of Micro-Beam SA, he was CEO of this company involved in high precision electric drive. Senior lecturer from 1998 and professor since 2003, he is currently director of Laboratory of Integrated Actuators. His research interests are in the field of new actuator design and associated electronic devices. In 2009, he is appointed Vice-Director of the Microengineering Institute in Neuchâtel until 2011. In 2013 the Federal Council has named him the the CTI commission in Bern. In 2014 he is appointed guest professor at Zhejiang University in China. In 2017, the lab is granted by the Werner Siemens Foundation of an amount of 12 millions CHF in order to set up a new Center for Artificial Muscules. Since 2018, he is Expert with Innosuisse, the new Swiss Innovation Agency. http://scholar.google.com/citations?hl=fr&user=V2onuO8AAAAJ https://actu.epfl.ch/news/a-12-million-franc-donation-to-create-a-center-for/ Florian Karl RichterCurriculum vitae You can download my CV here
ResearchResearch Fields Ergodic Theory, Combinatorics, Number TheoryList of Publications Open-access preprints and e-prints of all my publications are freely available on arXiv ↗ .An inverse theorem for sumsets of sets of positive density in the integersEthan Ackelsberg, Florian K. Richter submitted, 117 pageslink ↗Weighted averages of arithmetic functions and applications to equidistributionVitaly Bergelson, Michael Reilly, Florian K. Richter submitted, 29 page
Claudia Rebeca Binder SignerNée à Montréal, Claudia R. Binder est d’origine canadienne, suisse et colombienne. Elle grandit entre la Suisse et la Colombie. Alumni de l’ETH de Zurich, elle y obtient un diplôme en biochimie et un doctorat en Sciences de l'environnement, de 1985 à 1996. Elle poursuit sa carrière avec un post doctorat à l'Université du Maryland, aux États-Unis, de 1996 à 1998, et travaille en qualité d’assistante-senior à l’ETH jusqu’en 2006, où elle se spécialise dans les systèmes humains-environnementaux. Elle est ensuite nommée Professeure assistante au Département de géographie de l'Université de Zurich, un poste qu’elle occupe jusqu’en 2009.
Elle obtient en 2009 le titre de Professeure ordinaire en Sciences systémiques à l’Université de Graz, en Autriche et rejoint en 2011 le Département de Géographie de l’Université de Munich, en Allemagne, en tant que Professeure ordinaire en relations humaines-environnementales. Elle intègre l’EPFL en mars 2016, où elle ouvre le Laboratoire de relations humaines-environnementales dans les systèmes urbains (HERUS), rattaché à la Chaire La Mobilière pour l’écologie urbaine et un mode de vie durable, au sein de la Faculté de l’environnement naturel, architectural et construit (ENAC).
Ses recherches portent sur l'analyse, la modélisation et l'évaluation de la transition des systèmes urbains vers la durabilité. Elle examine en particulier comment nous pouvons mieux comprendre la dynamique du métabolisme urbain, ce qui caractérise une ville durable et ce qui anime et entrave les processus de transformation. Elle explore ces sujets en combinant les domaines des sciences sociales, des sciences naturelles et de la science des données. Ses recherches portent sur l'alimentation, l'énergie, les modes de vie et les transports durables dans les systèmes urbains.
En Suisse, Binder a été nommé membre du Conseil de la recherche, Division des programmes du Fonds national suisse (FNS) en 2016 et fait partie du Comité directeur du Programme national de recherche 71 du FNS, "Gestion de la consommation d'énergie" et du Swiss Competence Centers for Energy Research (SCCER). Elle est également membre du comité directeur sur Sustainability Research des Académies suisses des sciences et des lettres. En 2019, elle a été élue membre du Conseil universitaire de l'Université de Munich (LMU).
A l’EPFL, Claudia R. Binder est la directrice académique du programme d’enseignement interdisciplinaire «Projeter Ensemble». Elle a été nommée membre de la Direction du Centre de l'énergie en 2018 et dirige depuis 2019 le groupe de travail sur la Stratégie énergétique et de durabilité de l’école.
Damir FilipovicDamir Filipovic holds the Swissquote Chair in Quantitative Finance and is Swiss Finance Institute Professor at the Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Prior to this, he was head of the Vienna Institute of Finance and professor at the University of Vienna. He previously held the chair of financial and insurance mathematics at the University of Munich, and he was on the faculty of Princeton University. He received his Ph.D. in mathematics from ETH Zurich in 2000. Damir Filipovic worked as a scientific consultant for the Swiss Federal Office of Private Insurance from 2003 to 2004. There he co-developed the Swiss Solvency Test, which defines the regulatory capital requirement for all Swiss based insurance companies and groups. He is on the editorial board of several academic journals. His research interests include the term structure of interest rates, credit and volatility risk, quantitative methods in risk management, and stochastic processes. His papers have been published in a variety of academic journals including the Journal of Financial Economics, Mathematical Finance, Finance and Stochastics, and the Annals of Applied Probability. He is the author of a textbook titled Term-Structure Models.
Pablo Antolin SanchezEnseignement et PhD Doctorant·es actuel·les Philipp Christoph Weder, Davor Dobrota A co-dirigé les thèses EPFL de Ondine Chanon Cours Analysis III MATH-202(c) Le cours étudie les concepts fondamentaux de l'analyse vectorielle et de l'analyse de Fourier-Laplace en vue de leur utilisation pour résoudre des problèmes pluridisciplinaires d'ingénierie scientifique. Analysis III (for IC) MATH-203(d) Le cours étudie les concepts fondamentaux de l'analyse vectorielle et de l'analys
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'.
