Damir FilipovicDamir Filipovic holds the Swissquote Chair in Quantitative Finance and is Swiss Finance Institute Professor at the Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. Prior to this, he was head of the Vienna Institute of Finance and professor at the University of Vienna. He previously held the chair of financial and insurance mathematics at the University of Munich, and he was on the faculty of Princeton University. He received his Ph.D. in mathematics from ETH Zurich in 2000. Damir Filipovic worked as a scientific consultant for the Swiss Federal Office of Private Insurance from 2003 to 2004. There he co-developed the Swiss Solvency Test, which defines the regulatory capital requirement for all Swiss based insurance companies and groups. He is on the editorial board of several academic journals. His research interests include the term structure of interest rates, credit and volatility risk, quantitative methods in risk management, and stochastic processes. His papers have been published in a variety of academic journals including the Journal of Financial Economics, Mathematical Finance, Finance and Stochastics, and the Annals of Applied Probability. He is the author of a textbook titled Term-Structure Models.
Christophe MoserChristophe Moser is Associate Professor of Optics and the Section Director in the Microengineering department at EPFL. He obtained his PhD at the California Institute of Technology in optical information processing in 2000. He co-founded and was the CEO of Ondax Inc (acquired by Coherent Inc.), Monrovia California for 10 years before joining EPFL in 2010. His current interests are ultra-compact endoscopic optical imaging through multimode fibers, multimode fiber lasers, retinal imaging and additive manufacturing via volumetric 3D printing with light. He is the co-founder of Composyt light lab in the field of head worn displays in 2014 (acquired by Intel Corp), Earlysight SA and Readily3D. He is the author and co-author of 75 peer reviewed publications and 45 patents.
Philip Neil GarnerEnseignement et PhD Doctorant·es actuel·les Yesmine Abdennadher, Mutian He, Elija Maria Vida A co-dirigé les thèses EPFL de Mohammadjavad Taghizadeh, Pierre-Edouard Jean Charles Honnet, Sibo Tong, Bastian Schnell, Alexandre Samuel Philippe Bittar, Louise Clothilde Coppieters De Gibson, Haolin Chen
Marion LeleuExpertise
BioinformaticsGenomicsHight-Throughput SequencingData Mining
Andreas PautzEnseignement et PhD Doctorant·es actuel·les Sofia Portolan, Michel Saliba, Bishal Torrente, Alexis Paul Boris Claude Dupont-Bembinoff, Cynthia Camila Güttlein A dirigé les thèses EPFL de Ting Zhu, Vladimir Vladimirov Brankov, Boris Aviv Hombourger, Damar Canggih Wicaksono, Petra Mala, Adolfo Rais, Valentyn Bykov, Daniel Jerôme Siefman, Evgeny Nikitin, Dionysios Chionis, Oskari Ville Pakari, Friederike Bostelmann, Jiani Gao, Efstathios Vlassopoulos, Alessandro Scolaro, Stefan Radman, Alexander Aures, Lubom
Mohamad Baker DiaI am currently a data scientist and machine learning course developer at the EPFL Extension School, where I am involved in the production of online learning materials, designing and leading workshops and hackathons, and promoting the EPFL Extension School data science and digital skills to a wide audience.My interests include different aspects of machine learning, coding and information theory, signal processing, and inference on graphical models. I received the B.E. degree in Electrical and Computer Engineering and the B.A. degree in Economics with distinctions concurrently in 2012 from the American University of Beirut (AUB), Lebanon. I received the M.Sc. degree in Communication Systems in 2014 and the Ph.D. degree in Computer and Communication Sciences in 2018 both from the Swiss Federal Institute of Technology (EPFL), Switzerland.Between 2018 and 2020, I was a research scientist at the Institute for Data Science (i4DS) in the University of Applied Sciences Northwestern Switzerland (FHNW), where I worked in collaboration with the European Space Agency (ESA) on the Euclid space mission. I was a visiting researcher at Nokia Bell Labs, Germany in 2017 where I worked on the design of a novel coding scheme for the high-speed fiber optical communication systems. I was also a R&D engineer at the European Technology Center of SONY, Germany in 2014 working on the standardization of digital terrestrial TV broadcasting receivers. In 2011, I did my undergraduate internship at the University of California, Berkeley U.S.A. where I contributed to the “Mobile Millennium” traffic-monitoring project.
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'
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.
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.
Nicolas WürschNicolas Wyrsch was born in 1960 and studied physics at the ETH Zurich. After obtaining his diploma in 1984 he joined the group of Prof. Shah at the Institute of Microtechnology (IMT) of in Neuchâtel to contribute to the development of a-Si:H solar cells, focusing on the study electronic properties of the material. After a stay at Princeton University he obtained his Ph.D. from the University of Neuchatel in 1991. Since then he is team leader in the laboratory of photovoltaics (PV-LAB) of the Ecole Polytechnique Fédérale de Lausanne. His interests and main activities are focused on particle sensors and imagers, the integration of photovoltaic systems in the electric grid, including storage and building energy management, and PV module energy efficiency and lifetime.
