Friedrich EisenbrandFriedrich Eisenbrand's main research interests lie in the field of discrete optimization, in particular in algorithms and complexity, integer programming, geometry of numbers, and applied optimization. He is best known for his work on efficient algorithms for integer programming in fixed dimension and the theory of cutting planes, which are an important tool to solve large scale industrial optimization problems in practice.
Before joining EPFL in March 2008, Friedrich Eisenbrand was a full professor of mathematics at the University of Paderborn. Friedrich received the Heinz Maier-Leibnitz award of the German Research Foundation (DFG) in 2004 and the Otto Hahn medal of the Max Planck Society in 2001.
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
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.
Mika Tapani GöösWebsite
https://theory.epfl.ch/mika/
Teaching & PhD PhD Students Valentin Imbach, Ziyi Guan, Artur Riazanov, Anastasiia Sofronova, Weiqiang Yuan Past EPFL PhD Students Maystre Gilbert Théodore Courses Computational complexity CS-524 In computational complexity we study the computational resources needed to solve problems and understand the relation between different types of computation. This course advances the students knowledge of computational complexity, and develop an understanding o Martin VetterliMartin Vetterli was appointed president of EPFL by the Federal Council following a selection process conducted by the ETH Board, which unanimously nominated him.
Professor Vetterli was born on 4 October 1957 in Solothurn and received his elementary and secondary education in Neuchâtel Canton. He earned a Bachelor’s degree in electrical engineering from ETH Zurich (ETHZ) in 1981, a Master’s of Science degree from Stanford University in 1982, and a PhD from EPFL in 1986. Professor Vetterli taught at Columbia University as an assistant and then associate professor. He was subsequently named full professor in the Department of Electrical Engineering and Computer Sciences at the University of California at Berkeley before returning to EPFL as a full professor at the age of 38. He has also taught at ETHZ and Stanford University.
Professor Vetterli has earned numerous national and international awards for his research in electrical engineering, computer science and applied mathematics, including the National Latsis Prize in 1996. He is a fellow of both the Association for Computing Machinery and the Institute of Electrical and Electronics Engineers and a member the US National Academy of Engineering. He has published over 170 articles and three reference works.
Professor Vetterli’s work on the theory of wavelets, which are used in signal processing, is considered to be of major importance by his peers, and his areas of expertise, including image and video compression and self-organized communication systems, are central to the development of new information technologies. As the founding director of the National Centre of Competence in Research on Mobile Information and Communication Systems, Professor Vetterli is a staunch advocate of transdisciplinary research.
Professor Vetterli knows EPFL inside and out. An EPFL graduate himself, he began been teaching at the school in 1995, was vice president for International Affairs and then Institutional Affairs from 2004 to 2011, and served as dean of the School of Computer and Communication Sciences in 2011 and 2012. In addition to his role as president of the National Research Council of the Swiss National Science Foundation, a position he held from 2013 to 2016, he heads the EPFL’s Audiovisual Communications Laboratory (LCAV) since 1995.
Professor Vetterli has supported more than 60 students in Switzerland and the United States in their doctoral work and makes a point of following their highly successful careers, whether it is in the academic or business world.
He is the author of some 50 patents, some of which were the basis for start-ups coming out of his lab, such as Dartfish and Illusonic, while others were sold (e.g. Qualcomm) as successful examples of technology transfer. He actively encourages young researchers to market the results of their work.
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.
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.
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).
Zoë HolmesTeaching & PhD PhD Students Ricard Puig, Sacha Lerch, Reyhaneh Aghaei Saem, Shao Hen Chiew, Weijie Xiong, Marc Sanz Drudis, Mehrad Sahebi, Manuel Rudolph Courses Quantum information theory PHYS-550 After recapping the basics of quantum theory from an informationtheoretic perspective, we will cover more advanced topics inquantum information theory. This includes introducing measures of quantum information, and developing a more advanced understanding quantum states, channels and measurement
Ricard Puig I VallsExpertise
I'm interested on Variational Quantum Algorithms, Quantum Simulation and Quantum Metrology and Sensing. Overall in general I love studying how we can exploit quantum resources to surpass the classical limits.
Expertise
I'm interested on Variational Quantum Algorithms, Quantum Simulation and Quantum Metrology and Sensing. Overall in general I love studying how we can exploit quantum resources to surpass the classical limits.
I obtained my BSc in Physics in 2022 from the Autonomous University of Bar
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.
Jan Sickmann HesthavenProf. Hesthaven received an M.Sc. in computational physics from the Technical University of Denmark (DTU) in August 1991. During the studies, the last 6 months of 1989 was spend at JET, the european fusion laboratory in Culham, UK. Following graduation, he was awarded a 3 year fellowship to begin work towards a Ph.D. at Riso National Laboratory in the Department of Optics and Fluid Dynamics. During the 3 years of study, the academic year of 1993-1994 was spend in the Division of Applied Mathematics at Brown University and three 3 months during the summer of 1994 in Department of Mathematics and Statistics at University of New Mexico. In August 1995, he recieved a Ph.D. in Numerical Analysis from the Institute of Mathematical Modelling (DTU). Following graduation in August 1995, he was awarded an NSF Postdoctoral Fellowship in Advanced Scientific Computing and was approinted Visiting Assistant Professor in the Division of Applied Mathematics at Brown University. In December of 1996, he was appointed consultant to the Institute of Computer Applications in Science and Engineering(ICASE) at NASA Langley Research Center (NASA LaRC). As of July 1999, he was appointed Assistant Professor of Applied Mathematics, in September 2000 he was awarded an Alfred P. Sloan Fellowship, as of July 2001 he was awarded a Manning Assistant Professorship, and in March 2002, he was awarded an NSF Career Award. In January 2003, he was promoted to Associate Professor of Applied Mathematics with tenure and in May 2004 he was awarded Philip J. Bray Award for Excellence in Teaching in the Sciences (the highest award given for teaching excellence in all sciences at Brown University). He was promoted to Professor of Applied Mathematics as of July 2005. From October 2006 to June 2013, he was the Founding Director of the Center for Computation and Visualization (CCV) at Brown University. As of October 2007, he holds the (honorary) title of Professor (Adjunct) at the Technical University of Denmark. In November 2009, he successfully defended his dr.techn thesis at the Technical University of Denmark and was rewarded the degree of Doctor Technices -- the highest academic distinction awarded based on ... substantial and lasting contributions that has helped to move the research area forward and penetrated into applications. As grant Co-PI he served from Aug 2010 to June 2013 as Deputy Director of the Institute of Computational and Experimental Research in Mathematics (ICERM), the newest NSF Mathematical Sciences Research Institute. After having spend his entire academic career at Brown University, Prof Hesthaven decided to pursue new challenges and joined the Mathematics Institute of Computational Science and Engineering (MATHICSE) at Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland in July 2013. In March 2014 he was elected SIAM Fellow for contributions to high-order methods for partial differential equations.
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.
Dominique BonvinDominique Bonvin is Professor and Director of the Automatic Control Laboratory of EPFL. He received his Diploma in Chemical Engineering from ETH Zürich, and his Ph.D. degree from the University of California, Santa Barbara. He worked in the field of process control for the Sandoz Corporation in Basel and with the Systems Engineering Group of ETH Zürich. He joined the EPFL in 1989, where his current research interests include modeling, control and optimization of dynamic systems. He served as Director of the Automatic Control Laboratory for the periods 1993-97, 2003-2007 and again since 2012, Head of the Mechanical Engineering Department in 1995-97 and Dean of Bachelor and Master Studies at EPFL for the period 2004-2011.
