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
Olivier CanévetEnseignement et PhD Cours Machine Learning for Engineers EE-613
Amaury Pierre Jiezhi WeiExpertise
Deep Learning, Computer Vision, Physics Informed Machine Learning, Graph Neural Networks
Amaury a obtenu son Master en Robotique de l'Ecole Polytechnique Federale de Lausanne (EPFL) en 2021. Avant de rejoindre IMOS, il a travaillé pendant plusieurs années en tant que Software Engineer chez Logitech Europe S.A. dans le domaine de la Réalité Virtuelle et Augmentée. Il a développé des algorithmes de 6DoF tracking pour appareils portables, développé le firmware et conçu la stratégie de testing industr
Stéphanie LacourStéphanie P. Lacour holds the Bertarelli Foundation Chair in Neuroprosthetic Technology in the School of Engineering at EPFL and leads the Laboratory for Soft Bioelectronic Interfaces. She received her PhD in Electrical Engineering from INSA de Lyon, France, and completed postdoctoral research at Princeton University and the University of Cambridge. She is the recipient of the 2006 MIT TR35, a University Research Fellowship of the Royal Society, European Research Council ERC Starting and POC Grants, and a SNSF-ERC Consolidator Grant. She was elected a 2015 Young Global Leader by the World Economic Forum.
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.
Silvestro MiceraEnseignement et PhD Doctorant·es actuel·les Johannes Sebastiaan Nieuwenhuis, Mouhamed Zorkot, Angela Braccia, Jonathan Muheim, Xiangyu Xu A dirigé les thèses EPFL de Elvira Pirondini, Andrea Crema, Marco Bonizzato, Sophie Marie Marthe Wurth, Edoardo D'Anna, Emanuele Formento, Jenifer Cléa Miehlbradt, Flavio Raschella, Nawal Kinany, Théo Lemaire, Marion Aimée Geneviève Badi-Dubois, Tristan Jean Robin Barjavel, Vincent Alexandre Mendez, Outman Akouissi, Giulia Dominijanni, Simone Romeni, Franklin Leong, Ele
Jamie PaikProf. Jamie Paik is founder and director of the Reconfigurable Robotics Lab (RRL) of Swiss Federal Institute of Technology (EPFL) and a core member of Swiss NCCR robotics group. The RRL leverages expertise in multi-material fabrication and smart material actuation for novel robot designs. She received her PhD in Seoul National University on designing humanoid arm and a hand while being sponsored by Samsung Electronics. This 7-DoF humanoid arm was the lightest in the literature at that time being 3.7kg including the 8-DoF hand. During her Postdoctoral positions in the Institut des Systems Intelligents et de Robotic in Universitat Pierre Marie Curie, Paris VI, she developed laparoscopic tools named JAiMY that are internationally patented and commercialized now by Endocontrol-medical.com. At Harvard University’s Microrobotics Laboratory, she started developing unconventional robots that push the physical limits of material and mechanisms. Her latest research effort is in soft robotics including self-morphing Robogami (robotic origami) that transforms its planar shape to 2D or 3D by folding in predefined patterns and sequences, just like the paper art, origami.
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.
Loris Di NataleExpertise
(Deep) Machine Learning, (Deep) Reinforcement Learning, Building Control
