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'
Maude GirardinEnseignement et PhD Cours Algèbre linéaire (pour CMS) PREPA-002 Le but du cours est de familiariser les étudiants avec les notions fondamentales de l'algèbre linéaire à travers leur étude géométrique en dimension 3. Analyse A (pour MAN) PREPA-031(a) Ce cours donne les outils de base pour le calcul algébrique et pour la résolution d'équations et d'inéquations sur les nombres réels et complexes. Le cours explore l'étude des fonctions spéciales et sert de base au cours de calcul
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.
Maria BrbicMaria Brbic is an assistant professor in computer science at EPFL. Prior to joining EPFL, Maria was a postdoctoral researcher in Computer Science at Stanford University working with Jure Leskovec. She received her PhD degree from University of Zagreb in 2019, while also researching at Stanford University and University of Tokyo. Her research was awarded with the Fulbright Scholarship, L’Oreal UNESCO for Women in Science Scholarship, Branimir Jernej award for outstanding publication in biology and biomedicine, and Josip Loncar Silver Plaque award for the best doctoral dissertation. She has been named a Rising Star in EECS by MIT in 2021. Her research is focused on developing new machine learning methods and applying her methods to advance biomedical research.
Drazen DujicDrazen Dujic is an Associate Professor and Head of the Power Electronics Laboratory at EPFL. He received the Dipl.Ing. and MSc degrees from the University of Novi Sad, Serbia in 2002 and 2005, respectively, and the PhD degree from Liverpool John Moores University, UK in 2008. From 2003 to 2006, he was a Research Assistant with the Faculty of Technical Sciences at University of Novi Sad. From 2006 to 2009, he was a Research Associate with Liverpool John Moores University. After that he moved to industry and joined ABB Switzerland Ltd, where from 2009 to 2013, he was Scientist and then Principal Scientist with ABB Corporate Research Center in Baden-Dättwil, and from 2013 to 2014 he was R&D Platform Manager with ABB Medium Voltage Drives in Turgi. He joined EPFL in 2014 as Tenure Track Assistant Professor and was promoted to Associate Professor in 2021. His research interests include the areas of design and control of advanced high power electronic systems and high-performance drives, predominantly for the medium voltage applications related to electrical energy generation, conversion and storage. He has authored or coauthored more than 150 scientific publications and has filed 16 patents. In 2018 he received EPE Outstanding Service Award from European Power Electronics and Drives Association and in 2014 the Isao Takahashi Power Electronics Award for Outstanding Achievement in Power Electronics. He is Senior Member of IEEE, and serves as Associate Editor for IEEE Transactions on Power Electronics, IEEE Transactions on Industrial Electronics and IET Electric Power Applications. He is Chairman of the Swiss IEEE Power Electronics Society (PELS) Chapter and IEEE PELS R8 Chair.
Fabrizio SossanExpertise
Mathematical Modelling, Forecasting and Optimization for Power System Applications
Enseignement et PhD Doctorant·es actuel·les Keyu Jia A co-dirigé les thèses EPFL de Yihui Zuo, Mohsen Kalantar Neyestanaki, Rahul Kumar Gupta Cours Energy storage systems EE-466 Ce cours présente les principales technologies de stockage d'énergie, leurs attributs, leurs modèles mathématiques et leurs applications (stationnaires et mobiles), de la conception à l'exploitation et au contrôle, avec un
Stefano Francesco BurzioExpertise
Analyse et modélisation des phénomènes naturels non linéaires. équations aux différentielles partielles hyperboliques. Méthodes des éléments finis.
Enseignement et PhD Cours Dynamic finite element analysis of structures ME-473 Le cours présente l'analyse numérique des structures en trois dimensions en utilisant la méthode des éléments finis dans le cadre de l'élasticité linéaire. Les étudiants acquerront une maîtrise des techniques numériques les plus couramment utilisées en dynami
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,
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.
Florian Lucas JatonFlorian Jaton is a researcher and lecturer at EPFL (College of Humanities) and at the University of Lausanne (Faculty of Social and Political Sciences). He previously worked at the Donald Bren School of Information and Computer Science at the University of California, at the Centre de sociologie de l'innovation at Mines Paris, and at the Geneva Graduate Institute of International and Development Studies. His research interests are the sociology of algorithms, the philosophy of mathematics, and the history o
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.
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.
Chen LiuI am a PhD candidate at the School of Computer and Communication Sciences (IC), École Polytechnique Fédérale de Lausanne (EPFL), supervised by Prof. Sabine Süsstrunk and co-supervised by Dr. Mathieu Salzmann. Previously, I obtained my Master Degree from École Polytechnique Fédérale de Lausanne (EPFL) in 2017 and Bachelor Degree from Tsinghua University in 2015, both in Computer Science.
