Andrés Ignacio Cristi EspinosaExpertise
- Online Algorithms & Sequential Decision-Making- Algorithmic Game Theory- Mechanism & Market Design
Teaching & PhD PhD Students Jiechen Zhang, Aruzhan Amanbayeva Courses Algorithmic game theory MGT-435 We will study mathematical models of the interplay between algorithms and strategic behavior. We cover fundamental concepts from game theory and mechanism design, including Nash equilibria, the price of anarchy, auctions and market design, incentive compatibility, and online learn
Franco TufoTeaching & PhD Courses Mobility engineering CIVIL-451 Analyze and diagnose a situation from the urban planning and mobility points of view. Define strategies for achieving these objectives. Development of the most promising concepts.
Jack Richard WilliamsTeaching & PhD Courses Negotiation techniques MGT-466 This course is designed to give you a practical, hands-on opportunity to learn the basics of negotiating, self leadership and the impact of culture. Strategies and techniques are presented and practiced that will enable you to develop your skills and become a confident negotiator.
Yujia ZhangExpertise
Dropletronics: microscale droplet-based modular iontronics (e.g., batteries, diodes, transistors, memristors and circuits)Bioiontronics and bioelectronicsFunctional synthetic, cellular and hybrid tissuesBioengineering and human-machine interfaceAdvanced manufacturing of soft and living matter across multiple scales
2026 Masters Semester Project/Thesis, PhD and Postdoc Positions
Many opportunities exist in microengineering, bioengineering, materials science, microrobots, programming and AI; please
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.
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.
Lénaïc ChizatTeaching & PhD PhD Students Javier Esteban Maass Martinez Past EPFL PhD Students Guillaume Yitian Wang Courses Computational optimal transport MATH-528 Computational aspects of measure transportation, from classical optimal transport to modern denoising diffusion models. Topics in machine learning MATH-520 Mathematical analysis of modern supervised machine learning techniques, with an emphasis on the mathematics of artificial neural networks.
Simon Elias BibriExpertise
• Sustainable cities• Smarter eco-cities• Sustainable smart cities• Artificial Intelligence of Things (AIoT) • Generative Artificial Intelligence of Things (GAIoT)• Foundation Models (FMs) • Quantum Generative Artificial Intelligence (QGAI)• Urban Digital Twins (UDTs)• Urban Brain (UB) • Smart Circular Metabolism• Urban planning and design• Environmental sustainability and climate resilience• Sustainable smart energy• Sustainable smart transportation• Sustainable smart waste and water management•
Olga FinkTeaching & PhD PhD Students Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei Past EPFL PhD Students Ismail Nejjar, Mengjie Zhao Courses Data Science for infrastructure condition monitoring CIVIL-332 The course will cover the relevant steps of data-driven infrastructure condition monitoring, starting from data acquisition, going through the steps pre-processing of real
Keivan Faghih NiresiExpertise
Computational sensing/imaging, Inverse problems, Signal processing, Graph neural networks, Domain adaptation.
Keivan is a PhD student at école Polytechnique Fédérale de Lausanne (EPFL). He joined the Intelligent Maintenance and Operations Systems (IMOS) Lab under the supervision of Prof. Olga Fink in February 2023.Prior to joining EPFL, he obtained his master's degree from the Institute of Communications Engineering, College of Electrical Engineering and Computer Science, National Tsing Hua Univer
Anna Maria MadduxAnna M. Maddux holds a Bachelor's of Science in Mathematics and in Economics, both from the Albert-Ludwigs-University of Freiburg, as well as a Master's of Science in Statistics from ETH Zürich. In her master's thesis at the automatic control laboratory (Ifa) at ETH she developed a data-driven technique to learn the underlying utilities driving agents' behaviour in multi-agent games. Her research interests lie in the fields of game theory, optimization with a particular focus on learning in multi-agent systems.
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.
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
Dario FloreanoProf. Dario Floreano is director of the Laboratory of Intelligent Systems at the Swiss Federal Institute of Technology Lausanne (EPFL). Since 2010, he is the founding director of the Swiss National Center of Competence in Robotics, a research program that brings together more than 20 labs across Switzerland. Prof. Floreano holds an M.A. in Vision, an M.S. in Neural Computation, and a PhD in Robotics. He has held research positions at Sony Computer Science Laboratory, at Caltech/JPL, and at Harvard University. His main research interests are Robotics and A.I. at the convergence of biology and engineering. Prof. Floreano made pioneering contributions to the fields of evolutionary robotics, aerial robotics, and soft robotics. He served in numerous advisory boards and committees, including the Future and Emerging Technologies division of the European Commission, the World Economic Forum Agenda Council, the International Society of Artificial Life, the International Neural Network Society, and in the editorial committee of several scientific journals. In addition, he helped spinning off two drone companies (senseFly.com and Flyability.com) and a non-for-profit portal on robotics and A.I. (RoboHub.org). Books
Manuale sulle Reti Neurali, il Mulino (in Italian), 1996 (first edition), 2006 (second edition)Evolutionary Robotics, MIT Press, 2000
Bio-Inspired Artificial Intelligence, MIT Press, 2008
Flying Insects and Robots, Springer Verlag, 2010
Denis GilletDenis Gillet received the Diploma in Electrical Engineering from the Swiss Federal Institute of Technology in Lausanne (EPFL) in 1988, and the Ph.D. degree in Information Systems also from the EPFL in 1995. During 1992 he was appointed as Research Fellow at the Information Systems Laboratory of Stanford University in the United States. He is currently Maître d'enseignement et de recherche at the EPFL School of Engineering, where he leads the React research group. His current research interests include Technologies Enhanced Learning (TEL), Human Computer Interaction (HCI), Human Devices Interaction (HDI) and Optimal Coordination of Complex and Distributed Systems. Denis Gillet is affiliated at EPFL with the Center for Intelligent Systems and the Center for Digital Education.
