Hervé BourlardTeaching & PhD Past EPFL PhD Students Astrid Hagen, Katrin Weber, Todd Stephenson, Jitendra Ajmera, Shajith Ikbal, Mathew Magimai Doss, Mohamed Faouzi Benzeghiba, Mark Barnard, Yann Rodriguez, Hemant Misra, Christos Dimitrakakis, Guillaume Lathoud, Alexei Pozdnoukhov, Agnès Just, Mikaela Keller, Norman Hoon Thian Poh, Dong Zhang, Florent Monay Michaud, Pedro Manuel Da Silva Quelhas, Kevin Smith, Silèye Oumar Ba, Bertrand Mesot, Hamed Ketabdar, David Grangier, Guillermo Aradilla, Jean-François Paiement, Nico
Michaël UnserExpertise
Image Processing, Medical Imaging, Biological Imaging, Wavelets, Splines, Multiresolution
Michael Unser is Full Professor with EPFL’s school of Engineering and the academic director of EPFL's Center for Imaging, Lausanne, Switzerland. His primary areas of investigation are signal processing, biomedical imaging and applied functional analysis. He is internationally recognized for his research contributions to sampling theory, wavelets, the use of splines for image processing, stochastic processes,
François MaréchalPh D. in engineering Chemical process engineer
Researcher and lecturer in the field of computer aided process and energy systems engineering.
Lecturer in the mechanical engineering, electrical engineering and environmental sciences engineering in EPFL.
I'm responsible for the Minor in Energy of EPFL and I'm involved in 3 projects of the Competence Center in Energy and Mobility (2nd generation biofuel, Wood SOFC, and gas turbine development with CO2 mitigation) in which i'm contributing to the energy conversion system design and optimisation.
Short summary of my scientific carrer
After a graduation in chemical engineering from the University of Liège, I have obtained a Ph. D. from the University of Liège in the LASSC laboratory of Prof. Kalitventzeff (former president of the European working party on computer aided process engineering). This laboratory was one of the pioneering laboratory in the field of Computer Aided Process Engineering.
In the group of Professor Kalitventzeff, I have worked on the development and the applications of data reconciliation, process modelling and optimisation techniques in the chemical process industry, my experience ranges from nuclear power stations to chemical plants. In the LASSC, I have been responsible from the developments in the field of rational use of energy in the industry. My first research topic has been the methodological development of process integration techniques, combining the use of pinch based methods and of mathematical programming: e.g. for the design of multiperiod heat exchanger networks or Mixed integer non linear programming techniques for the optimal management of utility systems. Fronted with applications in the industry, my work then mainly concentrated on the optimal integration of utility systems considering not only the energy requirements but the cost of the energy requirements and the energy conversion systems. I developed methods for analysing and integrating the utility system, the steam networks, combustion (including waste fuel), gas turbines or other advanced energy conversion systems (cogeneration, refrigeration and heat). The techniques applied uses operation research tools like mixed integer linear programming and exergy analysis. In order to evaluate the results of the utility integration, a new graphical method for representing the integration of the utility systems has been developed. By the use of MILP techniques, the method developed for the utility integration has been extended to handled site scale problems, to incorporate environmental constraints and reduce the water usage. This method (the Effect Modelling and Optimisation method) has been successfully applied to the chemical plants industry, the pulp and paper industry and the power plant. Instead of focusing on academic problems, I mainly developed my research based on industrial applications that lead to valuable and applicable patented results. Recently the methods developed have been extended to realise the thermoeconomic optimisation of integrated systems like fuel cells. My present R&D work concerns the application of multi-objective optimisation strategies in the design of processes and integrated energy conversion systems.
Since 2001, Im working in the Industrial Energy Systems Laboratory (LENI) of Ecole Polytechnique fédérale de Lausanne (EPFL) where Im leading the R&D activities in the field of Computer Aided Analysis and Design of Industrial Energy Systems with a major focus on sustainable energy conversion system development using thermo-economic optimisation methodologies. A part from the application and the development of process integration techniques, that remains my major field of expertise, the applications concern :
Rational use of water and energy in Industrial processes and industrial production sites : projects with NESTLE, EDF, VEOLIA and Borregaard (pulp and paper).Energy conversion and process design : biofuels from waste biomass (with GASNAT, EGO and PSI), water dessalination and waste water treatment plant (VEOLIA), power plant design (ALSTOM), Energy conversion from geothermal sources (BFE). Integrated energy systems in urban areas : together with SCANE and SIG (GE) and IEA annexe 42 for micro-cogeneration systems.
I as well contributed to the definition of the 2000 Watt society and to studies concerning the emergence of green technologies on the market in the frame of the Alliance for Global Sustainability.
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.
Guillaume Marie BlancTeaching & PhD Courses Martingales and Brownian motion MATH-330 Introduction to the theory of discrete-time martingales (optional stopping and convergence theorems) and its applications (gambler's ruin, branching processes, Pólya urns...). Introduction to Brownian motion.
Samy BengioExpertise
Large Language ModelsReasoningStatistical machine learningSpeech processingPerson authenticationMultimodal processingSequence processingArtificial neural networks, support vector machinesHidden markov models, gaussian mixture modelsetc
Expertise
Large Language ModelsReasoningStatistical machine learningSpeech processingPerson authenticationMultimodal processingSequence processingArtificial neural networks, support vector machinesHidden markov models, gaussian mixture modelsetc
Mission
Samy Bengio
Robert DalangRobert Dalang, né en 1961, a reçu le diplôme de Mathématicien-EPFL en 1983 et est lauréat du Prix Dommer. Il passe l'année 1985-86 à Cornell University (USA) comme chercheur invité. Il obtient le doctorat au Département de mathématiques de l'EPFL en 1987. Son domaine de spécialisation est la théorie des processeurs stochastiques. En 1987, Robert Dalang est nommé professeur assistant au Département de statistiques de l'Université de Californie à Berkeley (USA). En 1988, il reçoit une bourse post-doctorale du Fonds national scientifique américain et effectue des recherches sur les propriétés markoviennes de processus stochastiques à plusieurs paramètres. En 1990, il est nommé à Tufts University (Boston, USA). Il est promu professeur associé en mai 1993. Une partie importante de ses recherches se font dans le cadre de contrats avec le Fonds national scientifique américain et l'Office de la recherche de l'armée américaine. En collaboration avec le Prof. R. Cairoli du Département de mathématiques de l'EPFL, il a écrit un livre sur l'optimisation stochastique séquentielle publié en 1996 aux éditions John Wiley. M. Dalang est nommé professeur extraordinaire de probabilités au Département de mathématiques en 1995. Il y poursuit des travaux de recherche en processus stochastiques et probabilité appliquée et participe à l'enseignement des processus stochastiques, de la théorie des probabilités et des cours de mathématiques aux sections d'ingénieurs. Il dirige régulièrement des thèses de doctorats, est éditeur de plusieurs journaux de recherche mathématique et travail en collaboration avec des chercheurs de plusieurs universités européennes et américaines.
Michaela HirschmannTeaching & PhD PhD Students Patrick Hirling, Jonathan Petersson, Lucie Scharré Courses Astrophysics III : galaxy formation and evolution PHYS-465 Galaxy formation & evolution is about studying how galaxies in our Universe come into existence, how they evolve and what shapes their properties. This course describes the observational facts of galaxies and the various processes of galaxy evolution as seen from theoretical/numerical models. General physics : thermodynamics (English) P
Jan SkaloudExpertise
Satellite positioning, inertial and integrated navigation Sensor orientation and calibration, attitude determination Mobile mapping, airborne laser scanning Adjustment methods, Kalman Filtering
Mission
Teaching in 3 EPFL sections and 2 faculties, director of ESO lab.
Books / Monographs J. Skaloud and M. Cramer, «Data Capture,» in GIS Handbook, W. Kresse and D. Danko, Eds. Springer, 2011. D. Lichti and J. Skaloud, «Registration and Calibration,» in Airborne and terrestrial laser scanning, H.-G. Ma
Thomas MountfordTeaching & PhD Past EPFL PhD Students Damien Gauthier, Samir Brahim Belhaouari, Driss Baraka, Daniel Rodrigues Valesin, Samuel Schöpfer, Kamran Kalbasi, Jacques Saliba, Hao Xue, Keming Chen Past EPFL PhD Students as codirector Guillaume Charles Woessner Courses Analysis I MATH-101(d) Study the fundamental concepts of analysis, and the differential and integral calculus of real-valued functions of one real variable. Markov chains MATH-332 The course follows the text of Norris
Michael Christoph GastparMichael Gastpar is a (full) Professor at EPFL. From 2003 to 2011, he was a professor at the University of California at Berkeley, earning his tenure in 2008.
He received his Dipl. El.-Ing. degree from ETH Zürich, Switzerland, in 1997 and his MS degree from the University of Illinois at Urbana-Champaign, IL, USA, in 1999. He defended his doctoral thesis at EPFL on Santa Claus day, 2002. He was also a (full) Professor at Delft University of Technology, The Netherlands.
His research interests are in network information theory and related coding and signal processing techniques, with applications to sensor networks and neuroscience.
He is a Fellow of the IEEE. He is the co-recipient of the 2013 Communications Society & Information Theory Society Joint Paper Award. He was an Information Theory Society Distinguished Lecturer (2009-2011). He won an ERC Starting Grant in 2010, an Okawa Foundation Research Grant in 2008, an NSF CAREER award in 2004, and the 2002 EPFL Best Thesis Award. He has served as an Associate Editor for Shannon Theory for the IEEE Transactions on Information Theory (2008-11), and as Technical Program Committee Co-Chair for the 2010 International Symposium on Information Theory, Austin, TX.
Kamiar AminianKamiar Aminian received the M.S. degree in electrical engineering in 1982, the Ph.D degree in biomedical engineering in 1989 and the Postgraduate degree on technical computing in 1993 from Ecole Polytechnique Fédérale de Lausanne (EPFL). He was assistant professor (1994-1996) with Sharif University of Technology (Tehran). He joint EPFL in 1996 where he is currently Professor of medical instrumentation and the director of the Laboratory of Movement Analysis and Measurement in the Institute of Bioengineering of EPFL. His research interests include methodologies for human movement monitoring and analysis in real world conditions mainly based on wearable technologies and inertial sensors with emphasis on gait, physical activity and sport. His research aims to perform outcome evaluation in orthopaedics, to improve motor function and intervention programs in aging and patients with movement disorders and pain, and to identify metrics of performance in sport science.
Kamiar Aminian is a member of the International Society of Posture and Gait Research, the Institute of Electrical and Electronics Engineers, the European Society of Movement Analysis in Adults and Children, the Prevention of fall Network Europe, the Intentional Society of Biomechanics and the President of the 3D analysis of the human movement group. He is author or co-author of more than 450 scientific papers published in reviewed journals and presented at international conferences and holds 10 patents related to medical devices.
Full CV
ORCID
Delphine PreissmannTeaching & PhD Courses Brain, mind and society HUM-256 This course aims to address topics related to research on brain causes of human actions. The course will introduce to fundamental concepts in psychology, cognitive and social neurosciences and the links between brain and mental illness. Health A: Innovation, Equity, Sustainability HUM-125(a) The course provides an interdisciplinary examination of key global health challenges, focusing on biomedical innovations, pharmaceut
Petr MotlicekTeaching & PhD PhD Students Shashi Kumar Past EPFL PhD Students as codirector Subhadeep Dey, Weipeng He, Juan Pablo Zuluaga Gomez Courses Digital Speech and Audio Coding EE-719 The goal of this course is to introduce the engineering students state-of-the-art speech and audio coding techniques with an emphasis on the integration of knowledge about sound production and auditory perception through signal processing techniques.
Sébastien MarcelExpertise
image processing, pattern recognition, machine learning, biometrics
Current work
Face recognitionSpeaker recognitionMobile biometrics ( http://www.mobioproject.org )Spoofing ( http://www.tabularasa-euproject.org )Biometrics evaluation and testing ( http://www.beat-eu.org )
Sébastien Marcel is the head of the Biometrics group and senior research scientist at the Idiap Research Institute (CH), where he leads a research team and conducts research on biometrics and more particularly face recognition, Nicolas Henri Bernard FlammarionNicolas Flammarion is a tenure-track assistant professor in computer science at EPFL. Prior to that, he was a postdoctoral fellow at UC Berkeley, hosted by Michael I. Jordan. He received his PhD in 2017 from Ecole Normale Superieure in Paris, where he was advised by Alexandre d’Aspremont and Francis Bach. In 2018 he received the prize of the Fondation Mathematique Jacques Hadamard for the best PhD thesis in the field of optimization. His research focuses primarily on learning problems at the interface of machine learning, statistics and optimization.
Jeremy LuterbacherExpertise
Biomass conversion Heterogeneous catalysis
See: https://www.epfl.ch/labs/lpdc/luterbacher/ Education Postdoc | Chemical Engineering 2014 – 2014 Univsersity of Wisconsin-Madison PhD | Chemical Engineering 2012 – 2012 Cornell University Master | Chemical Engineering 2010 – 2010 Cornell University Master | Chemical Engineering 2007 – 2007 �cole Polytechnique F�d�rale de Lausanne Bachelor | Chemistry and Ch 