Olivier Pierre ChételatEnseignement et PhD Cours Sensors in medical instrumentation EE-511 Principes fondamentaux et méthodes d'acquisition de signaux physiologiques. Techniques de capteurs avec électrodes, optiques, résistifs, capacitifs, inductifs et piezoélectrique utilisées pour la détection et la conversion d'information physiologique en signaux électriques. Dispositifs médicaux.
Katia GalanExpertise
Histology, genomics, cosec and BSO
Aude BillardExpertise
Machine LearningRoboticsMechatronicsDynamical SystemsComputational Neuroscience
Enseignement et PhD Doctorant·es actuel·les Hanli Zhang, Maximilian Schmitz, Luyin Hu, Baiyu Peng, Erfan Etesami, Sthithpragya Gupta, Kuanqi Cai A dirigé les thèses EPFL de Eric Sauser, Sylvain Calinon, Micha Hersch, Florent Günter, Biljana Petreska von Ritter-Zahony, Basilio Noris, Elena Gribovskaya, Seyed Mohammad Khansari Zadeh, Seungsu Kim, Ashwini Shukla, Klas Jonas Alfred Kronander, Luka Lukic, Miao Li, Ravin L
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.
Bernard SchneiderEnseignement et PhD Doctorant·es actuel·les Yesica Gloria, Christian Schellhaas A dirigé les thèses EPFL de Vanessa Laversenne, Sameer Mohammad Khaleel Nazeeruddin, Emma Charlotta Källstig A co-dirigé les thèses EPFL de Philippe Guillaume Coune, Emilda Pino, Elisabeth Anne Dirren, Aurélien Lathuilière, Wojciech Janusz Bobela, Lu Zheng, Cylia Cloé Rochat Cours Methods: from disease models to therapy BIOENG-518 Ce cours décrira les méthodes qui sont à la base des approches translationnelles
Friedhelm Christoph HummelExpertise
Stroke recoveryHealthy AgingMotor ControlMotor LearningCognitive ControlNeuroplasticityNon-invasive Brain StimulationStructural and functional NeuroimagingConnectivity
Enseignement et PhD Doctorant·es actuel·les Maria Ploumitsakou, Simona Losacco, Fabienne Windel, Andrea Protani, Stavroula Skarvelaki, Wei Chung Hsu, Rebecca Jane Jones, Beatrice Lugli, Thomas Paul, Paul de Fontenay, Michele Di Ponzio, Léa Kim-mi Ho Dac, Dong Jin Sung, Andrea Nuti, Greta Carnevali A dirigé les thèses EPFL de Rober
Mackenzie MathisCenter for NeuroprostheticsEPFL ELLIS Unit Faculty MemberCenter for Intelligent Systems
Sofia Charlotta OlhedeSofia Olhede is a professor of Statistics at EPFL in Switzerland. She joined UCL prior to this in 2007, before which she was a senior lecturer of statistics (associate professor) at Imperial College London (2006-2007), a lecturer of statistics (assistant professor) (2002-2006), where she also completed her PhD in 2003 and MSci in 2000. She has held three research fellowships while at UCL: UK Engineering and Physical Sciences Springboard fellowship as well as a five-year Leadership fellowship, and now holds a European Research Council Consolidator fellowship. Sofia has contributed to the study of stochastic processes; time series, random fields and networks. Sofia was part of the multi-institutional team that set up the UK national data science institute, the Alan Turing Institute. She organised and served as chair of the science committee that developed the initial 500 000 pounds scientific programme of the institute; peer-reviewing over 100 workshop proposals and hosting over 30. She also chaired the first recruitment wave of the institute hiring 13 data scientists as a multi-university recruitment drive. Sofia was a member of the Royal Society and British Academy Data Governance Working Group, and the Royal Society working group on machine learning. Most recently she was one of 3 commissioners on a law society commission on the usage of algorithms in the justice system.
Alexander MathisAlexander studied pure mathematics with a minor in logic and theory of science at the Ludwig Maximilians University in Munich. For his PhD also at LMU, he worked on optimal coding approaches to elucidate the properties of grid cells. As a postdoctoral fellow with Prof. Venkatesh N. Murthy at Harvard University and Prof. Matthias Bethge at Tuebingen AI, he decided to study olfactory behaviors such as odor-guided navigation, social behaviors and the cocktail party problem in mice. During this time, he increasingly got interested sensorimotor behaviors beyond olfaction and started working on proprioception, motor adaption, as well as computer vision tools for measuring animal behavior.
In his group, he is interested in elucidating how the brain gives rise to adaptive behavior. One of the major goals is to synthesize large datasets into computationally useful information. For those purposes, he develops algorithms and systems to analyze animal behavior (e.g. DeepLabCut), neural data, as well as creates experimentally testable computational models.
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