Boi FaltingsProfessor Faltings joined EPFL in 1987 as professor of Artificial Intelligence. He holds a PhD degree from the University of Illinois at Urbana-Champaign, and a diploma from the ETHZ. His research has spanned different areas of intelligent systems linked to model-based reasoning. In particular, he has contributed to qualitative spatial reasoning, case-based reasoning (especially for design problems), constraint satisfaction for design and logistics problems, multi-agent systems, and intelligent user interfaces. His current work is oriented towards multi-agent systems and social computing, using concepts of game theory, constraint optimization and machine learning. In 1999, Professor Faltings co-founded Iconomic Systems, a company that developed a new agent-based paradigm for travel e-commerce. He has since co-founded 5 other startup companies and advised several others. Prof. Faltings has published more than 150 refereed papers on his work, and participates regularly in program committees of all major conferences in the field. He has served as associate editor of of the major journals, including the Journal of Artificial Intelligence Research (JAIR) and the Artificial Intelligence Journal. From 1996 to 1998, he served as head of the computer science department.
Bernard MoretBernard M.E. Moret was born in Vevey, Switzerland, received baccalauréats in Latin-Greek and Latin-Mathematics, then did a Diploma in Electrical Engineering at EPFL. After working for 2 years for Omega and Swiss Timing on the development of real-time OS for sports applications, he left for the US. He received his PhD in Electrical Engineering from the U. of Tennessee in 1980 and joined the Department of Computer Science at the University of New Mexico (UNM) that fall. He served as Chairman of the department from 1991 till 1993 and eventually retired in summer 2006 to join the School of Computer and Communication Sciences at EPFL. (You can read about his work at UNM on his (archived) personal and laboratory web pages at UNM.) He was appointed group leader for phylogenetics at the Swiss Institute for Bioinformatics (SIB). From 2009 until his retirement, he was also in charge of the BS and MS programs in Computer Science and Associate Dean for Education. He founded the ACM Journal of Experimental Algorithmics (JEA) and served as its Editor-in-Chief for 7 years; he also helped found the IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), where he served as Associate Editor until 2008. He founded the annual Workshop on Algorithms in Bioinformatics (WABI) and chairs its steering committee, and he serves on the steering committee of the Workshop on Algorithm Engineering and Experiments (ALENEX). Until summer 2008, he chaired the Biodata Management and Analysis (BDMA) study section of the US National Institutes of Health (NIH); now he is a charter member of the NIH College of Reviewers. He led a team of over 50 biologists, computer scientists, and mathematicians in the CIPRES (Cyber Infrastructure for Phylogenetic Research) project, funded by the US National Science Foundation (NSF) for US$ 12 million over 5 years. He has published nearly 150 papers in computational biology, under funding from the US NSF, the Alfred P. Sloan foundation, the IBM Corporation, the US NIH, the Swiss NSF, and SystemsX.ch. He is a Fellow of the ISCB (International Society for Computational Biology). His Erdös number is 2 and (as of 2020) his h-index is 48.
Frédéric CourbinAfter his studies in fundamental physics at the University of Paris-XI (Orsay, France), Frédéric Courbin carried out his PhD work between the Astrophysics Institute of the University of Liège (Belgium), Paris Observatory (France), and the European Southern Observatory (Germany). In 1999, he left Europe for three years, taking advantage of the clear skies of Chile to carry out his research using the brand new Very Large Telescope, constructed by Europe in the Atacama desert. In 2004, after two years of a Marie Curie fellowship at the University of Liège, he joint the Laboratory of Astrophysics, where he is now Professor. His main fields of activity are in observational cosmology and extragalactic astrophysics as well as in image and signal processing. In 2018, he was awarded an ERC Advanced Grant in connection with his work in cosmology with gravitational lenses. At EPFL, he is a member of the committee for the Physics Doctoral School since 2013 and has been the tutor of more than 30 PhD students. He is a member of the EPFL Council for the Faculty of Basic Sciences since 2018 and a member of the School Assembly since 2020.
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.
Nicolas MacrisNicolas Macris received the PhD degree in theoretical physics from EPFL and then pursued his scientific activity at the mathematics department of Rutgers University (NJ, USA). He then joined the Faculty of Basic Science of EPFL, working in the field of quantum statistical mechanics and mathematical aspects of the quantum Hall effect. Since 2005 he is with the Communication Theories Laboratory and Information Processing group of the School of Communication and Computer Science and currently works at the interface of statistical mechanics, information theory and error correcting codes, inference and learning theory. He held long-term visiting appointments and collaborations with the University College and the Institute of Advanced studies in Dublin, the Ecole Normale Supérieure de Lyon, the Centre de Physique Theorique Luminy Marseille, Paris XI Orsay, the ETH Zürich and more recently Los Alamos National Lab. CV and publication list.
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
