Olivier SauterTeaching & PhD PhD Students Cassandre Ekta Contré, Antonia Frank, Peizheng Zhang, Jean-Pierre Thomas Svantner, Cristina Venturini, Cosmas Quirin Lorenz Heiss, Daniel Perales Rios, Viacheslav Bochkarev, Jan Jakub Frybes, Paul Véronique Guillaume Devianne Past EPFL PhD Students Clemente Angioni, Petri Nikkola, Alberto Bottino, Andrei Martynov, Emiliano Fable, Costanza Zucca, Federico Felici, Dávid Wágner, Doohyun Kim, Anna Teplukhina, Mengdi Kong, Francesco Carpanese, Simon Van Mulders, Stefano Marchioni, F
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.
Sofia Charlotta OlhedeI am a professor of Statistics at EPFL. I did my PhD in Mathematics at Imperial College London, and graduated in 2003. I was an assistant professor (lecturer) at Imperial College London 2002-2006, and an associate professor (senior lecturer) 2006-2007. In 2007 I moved to University College London and became a full professor. I moved to EPFL in 2019, and in 2018 I became an Institute of Mathematical Statistics Fellow with citation “For seminal contributions to the theory and application of large and heteroge
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.
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
Mengjie ZhaoMengjie Zhao holds degrees in Computational Mechanics (MSc) with honors track and in Engineering Science (BSc) from the Technical University of Munich (TUM).
From the early years of her studies, Mengjie was fascinated by the modeling of multiphysics and multiscale systems. As a student research assistant at TUM and research intern at International Centre for Numerical Methods in Engineering (CIMNE), she gained a solid understanding of both the theoretical and algorithmic fundamentals as well as a wide range of applications. Through the BGCE project with the Elitenetzwerk Bayern (ENB), which dealt with the mesh sensitivity prediction with a deep neural network, she realized that leveraging data could bring physical modeling far beyond the current computational limits. Later, in her master's thesis in cooperation with Siemens, she turned to the reduced-order modeling with enforced physical invariants, which showed better accuracy and generality.
In her Ph.D., she would like to step towards a further combination of deductive research (modeling and simulation) and inductive (data-driven) research by embedding physics into machine learning.
Mario PaoloneMario Paolone received the M.Sc. (with honors) and the Ph.D. degree in electrical engineering from the University of Bologna, Italy, in 1998 and 2002, respectively. In 2005, he was appointed assistant professor in power systems at the University of Bologna where he was with the Power Systems laboratory until 2011. In 2010, he received the Associate Professor eligibility from the Politecnico di Milano, Italy. Since 2011 he joined the Swiss Federal Institute of Technology, Lausanne, Switzerland, where he is now Full Professor, Chair of the Distributed Electrical Systems laboratory and Head of the Swiss Competence Center for Energy Research (SCCER) FURIES (Future Swiss Electrical infrastructure). He was co-chairperson of the technical programme committees of the 9th edition of the International Conference of Power Systems Transients (IPST 2009) and of the 2016 Power Systems Computation Conference (PSCC 2016). He was chair of the technical programme committee of the 2018 Power Systems Computation Conference (PSCC 2018). In 2013, he was the recipient of the IEEE EMC Society Technical Achievement Award. He was co-author of several papers that received the following awards: best IEEE Transactions on EMC paper award for the year 2017, in 2014 best paper award at the 13th International Conference on Probabilistic Methods Applied to Power Systems, Durham, UK, in 2013 Basil Papadias best paper award at the 2013 IEEE PowerTech, Grenoble, France, in 2008 best paper award at the International Universities Power Engineering Conference (UPEC). He was the founder Editor-in-Chief of the Elsevier journal Sustainable Energy, Grids and Networks and was Associate Editor of the IEEE Transactions on Industrial Informatics. His research interests are in power systems with particular reference to real-time monitoring and operation, power system protections, power systems dynamics and power system transients. Mario Paolone is author or coauthor of over 300 scientific papers published in reviewed journals and international conferences.
