Johanni Michael BreaTeaching & PhD PhD Students Aude Maier, Lucas Louis Gruaz, Flavio Martinelli Courses Artificial intelligence and society HUM-286 This course integrates social sciences and humanities with engineering sciences, and introduces students to the social, technical and political issues surrounding artificial intelligence. Biological data science II : machine learning BIO-322 Students understand basic concepts and methods of machine learning. They can describe them in mathematical
Olivier CanévetExpertise
Computer Vision, Machine Learning, Deep Learning
Research engineer at the Idiap Research Institute. I am a research engineer at the Idiap Research Institute. I have a PhD from the école Polytechnique Fédérale de Lausanne doneunder the supervision of Dr François Fleuret. My research was funded by the Swiss National Science Foundation (DASH). I graduated from the French Engineering School TELECOM Bretagne (Brest) in 2012 and hold a Master in image processing from Université de Rennes1. I did a six-
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.
Loris Di NataleExpertise
(Deep) Machine Learning, (Deep) Reinforcement Learning, Building Control
Maria Giulia PretiMaria Giulia Preti received her Ph.D. in Bioengineering at Politecnico di Milano (Milan, Italy) in 2013, after her M. Sc. (2009) and B. Sc. (2007) in Biomedical Engineering, as well at Politecnico di Milano. During her Ph.D., mentored by Prof. Giuseppe Baselli, she focused on advanced techniques of brain magnetic resonance imaging, in particular she developed a method of groupwise fMRI-guided tractography, that revealed to be useful in the in-vivo investigation of the pathophysiological changes across the evolution of Alzheimers disease. For this project, she had been collaborating full-time with the hospital Fondazione Don Gnocchi in Milan (Magnetic Resonance Laboratory). In 2011, she was awarded a Progetto Rocca fellowship from MIT-Italy and spent a visiting research period at the MIT and Harvard Medical School (Boston, USA), under the supervision of Prof. Nikos Makris, where she could focus on the anatomical study of specific neruonal bundles.
She has joined Prof. Van De Ville group at EPFL as a post-doc in 2013. Her current research aims at understanding the connections between brain functionality and brain microscopic anatomy by using advanced techniques of Magnetic Resonance Imaging. In particular, she is working on functional MRI, functional connectivity, diffusion tensor imaging and tractography, integration of MRI with other techniques (e.g. EEG), and the application of these methods to several clinical contexts, e.g., epilepsy, Alzheimer's disease and mild cognitive impairment, multiple sclerosis, attention deficit hyperactivity disorder.
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.
Johannes GräffAcademic appointments
2013- Tenure Track Assistant Professor, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, School of Life Sciences, Brain Mind Institute.
2009-2013 Postdoctoral fellow, Massachusetts Institute of Technology (MIT), Cambridge, USA, Picower Institute for Learning and Memory.
2009 Postdoctoral associate, Swiss Federal Institute of Technology (ETHZ), Zürich, Switzerland, Brain Research Institute.
Education
2009 PhD in Neurosciences, Swiss Federal Institute of Technology (ETHZ), Zürich, Switzerland, Department of Biology, Brain Research Institute.
2005 Diploma (M.Sc. equivalent) in Biological Sciences, University of Lausanne, Switzerland, Faculty of Biology and Medicine, Department of Ecology and Evolution.
1998 Matura, Gymnasium Type B, Kantonsschule am Burggraben St. Gallen, Switzerland.
