Johanni Michael BreaEnseignement et PhD Doctorant·es actuel·les Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Cours Biological data science II : machine learning BIO-322 Les étudiants comprennent les concepts et méthodes de base d'apprentissage automatique. Ils savent les décrire en termes mathématiques et ils savent les appliquer aux données en utilisant un langage de haut niveau (julia/python/R). Intelligence artificielle et société HUM-286 Ce cours intègre les SHS avec les sciences de l'
Olivier CanévetEnseignement et PhD Cours Machine Learning for Engineers EE-613
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.
Berend SmitEnseignement et PhD Doctorant·es actuel·les Anastasia Blokhina, Raluca-Ana Kessler, Seyed Amirmohammad Elahi, Juliette Veronique Schleicher, Yutao Li, Xin Jin, Sara Bassetta, Beatriz Bueno Mouriño A dirigé les thèses EPFL de Samantha Lynn Anderson, Daniele Ongari, Andrzej Gladysiak, Seyedmohamad Moosavi, Arunraj Chidambaram, Bardiya Valizadeh, Stavroula Kampouri, Fatmah Ebrahim, Fatma Pelin Uran, Andres Adolfo Ortega Guerrero, Kevin Maik Jablonka, Elias Moubarak, Sauradeep Majumdar, Miriam Jasmin Pougin,
Loris Di NataleExpertise
(Deep) Machine Learning, (Deep) Reinforcement Learning, Building Control
Michele CeriottiMichele Ceriotti received his Ph.D. in Physics from ETH Zürich in 2010. He spent three years in Oxford as a Junior Research Fellow at Merton College. Since 2013 he leads the laboratory for Computational Science and Modeling in the Institute of Materials at EPFL. His research revolves around the atomic-scale modelling of materials, based on the sampling of quantum and thermal fluctuations and on the use of machine learning to predict and rationalize structure-property relations. He has been awarded the IBM Research Forschungspreis in 2010, the Volker Heine Young Investigator Award in 2013, an ERC Starting Grant in 2016, and the IUPAP C10 Young Scientist Prize in 2018.
Maria Giulia PretiEnseignement et PhD Doctorant·es actuel·les Flavia Petruso Cours Network Neuroscience: Methods & Applications EE-629
Yifan HuExpertise
Optimization, Operations Research, Reinforcement Learning
I am a Postdoc with Prof. Daniel Kuhn from EPFL and Prof. Andreas Krause from ETH Zurich. Prior to that, I got my PhD in Operations Research from University of Illinois at Urbana-Champaign, advised by Prof. Xin Chen and Prof. Niao He. My research interest lies in data-driven decision-making with problems arising from optimization, operations research, and statistics. See Research for research directions and Publication for papers.
