Quy Ong KhacEnseignement et PhD Doctorant·es actuel·les Hien Tran Thi, Ekaterina Poliukhina
Romain GuietExpertise
Development of BioImage Analysis workflows and algorithms to extract quantitative data from microscopy images.BioSample Preparation : in vitro cell, organoid, time-lapse, fixation, staining strategies, actin, mitochondria, fluorescent protein expressionBioImage Acquisition : Widefield, Confocal, Whole Slide Imaging, Super-resolution (SIM, STORM, STED), FRET, FRAP, FLIMBioImage Analysis: Colocalisation analysis, Deconvolution, Time-lapse , Whole Slide ImagingTools & Software: ImageJ/Fiji, QuPath, i
Olivier CanévetEnseignement et PhD Cours Machine Learning for Engineers EE-613
Bruno Emanuel Ferreira De Sousa CorreiaThroughout my PhD and postdoctoral studies I was trained in world-renowned laboratories and institutions in the United States of America (University of Washington and The Scripps Research Institute). Very early in my scientific career I found out my fascination about protein structure and function. My PhD studies evolved in the direction of immunogen design and vaccine engineering which sparked my interest in the many needs and opportunities in vaccinology and translational research. My efforts resulted in an enlightening piece of work where for the first time, computationally designed immunogens elicited potent neutralizing antibodies. During my postdoctoral studies I joined a chemical biology laboratory at the Scripps Research Institute. In this stage I developed novel chemoproteomics methods for the identification of protein-small molecule interaction sites in complex proteomes. In March 2015, I joined the École Polytechnique Fédérale de Lausanne (EPFL) – Switzerland as a tenure track assistant professor. The focus of my research group is to develop computational tools for protein design with particular emphasis in applying these strategies to immunoengineering (e.g. vaccine and cancer immunotherapy). The activities in my laboratory focus on computational design methods development and experimental characterization of the designed proteins. Our laboratory has been awarded with 2 prestigious research grants from the European Research Council. Lastly, I have been awarded the prize for best teacher of Life sciences in 2019.
Luciano Andres AbriataEnseignement et PhD Cours Basic and advanced NMR - Level 1 A (EPFL) CH-601(x) Basic and advanced NMR - Level 2 (EPFL) CH-703 The goal is to give a sound theoretical and practical foundation in NMR for various applications in research. PhD students and post-docs who have followed the course successfully should be able to perform modern multi-dimensional NMR experiments independently. Integrative structural biology for Life sciences BIO-643 Recombinant protei
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'
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,
Christoph KochEnseignement et PhD Doctorant·es actuel·les Léonard Léchot, Zhekai Jiang, Hanbit Lee A dirigé les thèses EPFL de Immanuel Trummer, Aleksandar Vitorovic, Milos Nikolic, Daniel Lupei, Mohammed El Seidy, Ioannis Klonatos, Mohammad Dashti Rahmat Abadi, Amir Shaikhha, Lionel Parreaux, Sachin Basil John, Zilu Tian A co-dirigé les thèses EPFL de David Kozhaya Cours Making intelligent things A CS-358(a) Le cours vise à enseigner le prototypage d'artefacts physiques intelligents et à résoudre des d
Jean-Paul Richard KneibEnseignement et PhD Doctorant·es actuel·les Oliver Pineda Suarez, Robert Daniel Kincaid, Ethan Daniel Tregidga, Belén Yu Irureta-Goyena Chang, Elisabeth Andréa Cécile Rachith, Shengyu He, Aurélien Thomas Mathieu Verdier, Timour Jestin A dirigé les thèses EPFL de Markus Rexroth, Luzius Gregor Kronig, Christoph Ernst René Schäfer, Vasileios Angelopoulos, Michaël Juillard, Amélie Tamone, Andrei Variu, Yoan Rappaz, Anne-Marlene Rüede, Jiaxi Yu, Daniel Felipe Forero Sanchez, Beauchesne Benjamin Emmanuel Nicola
David Richard HarveyEnseignement et PhD Doctorant·es actuel·les Ethan Daniel Tregidga, Felix Francisco Vecchi Cours Lecture series on scientific machine learning PHYS-754 Ce cours présente des travaux sur la façon dont les questions scientifiques peuvent être abordées à l'aide de l'apprentissage automatique. L'apprentissage automatique permet d'extraire des connaissances à partir de données de manière automatisée. Nous apprendrons à partir d'exemples concrets.
Volker GassFonction
Directeur, Initiatives Stratégiques - VPI
Enseignement et PhD A dirigé les thèses EPFL de Camille Sébastien Pirat, Florian Thibaut Gallien, Maxime Auchlin, Timothée Robert Sophus Frei, Tatiana Maillard
Anders MeibomAnders Meibom obtained his PhD in physics from the University of Southern Denmark in 1997. This was followed by two and a half years of PostDoc work at the Hawaii Institute for Geophysics and Planetology, where he conducted mineralogical studies of primitive chondritic meteorites. From 2000 to 2005, he was Research Associate in the Geological & Environmental Sciences, Stanford University, where he represented Stanford in the USGS-Stanford ion microprobe laboratory. In 2005, he became proifessor at the Muséum National dHistoire Naturelle in Paris. From 2006 to 2011 he was the director of the French national NanoSIMS laboratory. Since January 2012, he is professor at the EPFL in the School of Architecture, Civil and Environmental Engineering (ENAC). From April 2014, he is professor ad personam at the Institute of Earth Sciences, University of Lausanne.
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.
Colin Neil JonesColin Jones is an Associate Professor in the Automatic Control Laboratory at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland. He was a Senior Researcher at the Automatic Control Lab at ETH Zurich until 2011 and obtained a PhD in 2005 from the University of Cambridge for his work on polyhedral computational methods for constrained control. Prior to that, he was at the University of British Columbia in Canada, where he took a BASc and MASc in Electrical Engineering and Mathematics. Colin has worked in a variety of industrial roles, ranging from commercial building control to the development of custom optimization tools focusing on retail human resource scheduling. His current research interests are in the theory and computation of predictive control and optimization, and their application to green energy generation, distribution and management.
