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-
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.
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.
Elisa OricchioExpertise
Cancer geneticsMouse modelsTherapyStem cellsLymphoma
Teaching & PhD PhD Students Vamsi Krishna Polavarapu, Asli Ece Kasapoglu, Konstantina Georgakopoulou, Eleni Balli Past EPFL PhD Students Maria Christine Donaldson, Elena Battistello, Daniel Pereira Duarte, Frédérica Schyrr, Ruxandra-Andreea Lambuta, Aaron Simone Petruzzella, Jixing Zhong, Justine Epiney Courses Cancer biology I BIO-471 The course covers in detail molecular mechanisms of cancer development with emphasis on cell
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
Amaury Pierre Jiezhi WeiExpertise
Deep Learning, Computer Vision, Physics Informed Machine Learning, Graph Neural Networks
Amaury obtained his Master's degree in Robotics from the Federal Institute of Technology in Lausanne (EPFL) in 2021.Before joining IMOS, he worked for multiple years at Logitech Europe S.A. as a Software Engineer in the field of Augmented and Virtual Reality. He researched 6DoF tracking solutions for handheld devices, developed the firmware and designed the testing strategy for the MR Stylus MX Ink.During his
Andrea AblasserTeaching & PhD PhD Students Ekaterina Gorbacheva, Iris Arianna Dorschel, Tieliang Gan, Yu Meng Past EPFL PhD Students Simone Margret Haag, Sélène Glück, Marilena Wischnewski, Sophie Rivara, Natasha Samson Courses Immunology - advances and therapeutic implications BIO-479 The students acquire advanced level knowledge regarding the functioning of the (vertebrate) immune system. A strong focus is placed on the molecular mechanisms underlying innate and adaptive immune responses and their impl
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.
Loris Di NataleExpertise
(Deep) Machine Learning, (Deep) Reinforcement Learning, Building Control
Weizhe LiuI am a Ph.D. candidate at CVLAB, EPFL, under the supervision of Prof. Pascal Fua. Prior to that, I received the Master of Science degree from EPFL in 2017 and the Bachelor of Engineering degree from University of Electronic Science and Technology of China (UESTC) in 2014.
My research interests lie in the field of Computer Vision, Machine Learning and Robotics. My main focus is on developing algorithms to crowd analysis problem, including counting, localization and motion estimation. Recently, I also work on semantic segmentation, domain adaptation and learning with less supervision.
