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.
Emre TelatarI. Emre Telatar received the B.Sc. degree in electrical engineering from the Middle East Technical University, Ankara, Turkey, in 1986. He received the S.M. and Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, in 1988 and 1992 respectively. In 1992, he joined the Communications Analysis Research Department at AT&T Bell Laboratories (later Lucent Technologies), Murray Hill, NJ. He has been at the EPFL since 2000.
Emre Telatar was the recipient of the IEEE Information Theory Society Paper Award in 2001. He was a program co-chair for the IEEE International Symposium on Information Theory in 2002, and associate editor for Shannon Theory for the IEEE Information Theory Transactions from 2001 to 2004. He was awarded the EPFL Agepoly teaching prize in 2005.
Emre Telatar's research interests are in communication and information theories.
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.
Anthony Christopher DavisonAnthony Davison has published on a wide range of topics in statistical theory and methods, and on environmental, biological and financial applications. His main research interests are statistics of extremes, likelihood asymptotics, bootstrap and other resampling methods, and statistical modelling, with a particular focus on the first currently. Statistics of extremes concerns rare events such as storms, high winds and tides, extreme pollution episodes, sporting records, and the like. The subject has a long history, but under the impact of engineering and environmental problems has been an area of intense development in the past 20 years. Davison''s PhD work was in this area, in a project joint between the Departments of Mathematics and Mechanical Engineering at Imperial College, with the aim of modelling potential high exposures to radioactivity due to releases from nuclear installations. The key tools developed, joint with Richard Smith, were regression models for exceedances over high thresholds, which generalized earlier work by hydrologists, and formed the basis of some important later developments. This has led to an ongoing interest in extremes, and in particular their application to environmental and financial data. A major current interest is the development of suitable methods for modelling rare spatio-temporal events, particularly but not only in the context of climate change. Likelihood asymptotics too have undergone very substantial development since 1980. Key tools here have been saddlepoint and related approximations, which can give remarkably accurate approximate distribution and density functions even for very small sample sizes. These approximations can be used for wide classes of parametric models, but also for certain bootstrap and resampling problems. The literature on these methods can seem arcane, but they are potentially widely applicable, and Davison wrote a book joint with Nancy Reid and Alessandra Brazzale intended to promote their use in applications. Bootstrap methods are now used in many areas of application, where they can provide a researcher with accurate inferences tailor-made to the data available, rather than relying on large-sample or other approximations of doubtful validity. The key idea is to replace analytical calculations of biases, variances, confidence and prediction intervals, and other measures of uncertainty with computer simulation from a suitable statistical model. In a nonparametric situation this model consists of the data themselves, and the simulation simply involves resampling from the existing data, while in a parametric case it involves simulation from a suitable parametric model. There is a wide range of possibilities between these extremes, and the book by Davison and Hinkley explores these for many data examples, with the aim of showing how and when resampling methods succeed and why they can fail. He was Editor of Biometrika (2008-2017), Joint Editor of Journal of the Royal Statistical Society, series B (2000-2003), editor of the IMS Lecture Notes Monograph Series (2007), Associate Editor of Biometrika (1987-1999), and Associate Editor of the Brazilian Journal of Probability and Statistics (1987 2006). Currently he on the editorial board of Annual Reviews of Statistics and its Applications. He has served on committees of Royal Statistical Society and of the Institute of Mathematical Statistics. He is an elected Fellow of the American Statistical Assocation and of the Institute of Mathematical Statistics, an elected member of the International Statistical Institute, and a Chartered Statistician. In 2009 he was awarded a laurea honoris causa in Statistical Science by the University of Padova, in 2011 he held a Francqui Chair at Hasselt University, and in 2012 he was Mitchell Lecturer at the University of Glasgow. In 2015 he received the Guy Medal in Silver of the Royal Statistical Society and in 2018 was a Medallion Lecturer of the Institute of Mathematical Statistics.
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'.
Ali H. SayedAli H. Sayed is Dean of Engineering at EPFL, Switzerland, where he also leads the Adaptive Systems Laboratory. He has also served as Distinguished Professor and Chairman of Electrical Engineering at UCLA. He is recognized as a Highly Cited Researcher and is a member of the US National Academy of Engineering. He is also a member of the World Academy of Sciences and served as President of the IEEE Signal Processing Society during 2018 and 2019.
Dr. Sayed is an author/co-author of over 570 scholarly publications and six books. His research involves several areas
including adaptation and learning theories, data and network sciences, statistical inference, and multiagent systems.
His work has been recognized with several major awards including the 2022 IEEE Fourier Award, the 2020 Norbert Wiener Society Award and the 2015 Education Award from the IEEE Signal Processing Society, the 2014 Papoulis Award from the European Association for Signal Processing, the 2013 Meritorious Service Award and the 2012 Technical Achievement Award from the IEEE Signal Processing Society, the 2005 Terman Award from the American Society for Engineering Education, the 2005 Distinguished Lecturer from the IEEE Signal Processing Society, the 2003 Kuwait Prize, and the 1996 IEEE Donald G. Fink Prize. His publications have been awarded several Best Paper Awards from the IEEE (2002, 2005, 2012, 2014) and EURASIP (2015). He is a Fellow of IEEE, EURASIP, and the American Association for the Advancement of Science (AAAS); the publisher of the journal Science.
