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
Mahmut Selman SakarEnseignement et PhD Doctorant·es actuel·les Lorenzo Francesco John Noseda, Nikita Norkin, Elif Ezgi Inan, Houman Javaheri, Mehdi Ali Gadiri, Julian Leon Raub, Junsun Hwang A dirigé les thèses EPFL de Erik Mailand, Raquel Filipa Penacho Parreira, Murat Kaynak, Lucio Pancaldi-Giubbini, Fazil Emre Uslu, Matthias Rüegg, Ece Özelçi, Emilie Vuille-Dit-Bille A co-dirigé les thèses EPFL de Laura Joan Hermans, Sourabh Monnappa Kuppanda Jafri Cours Dynamical systems ME-221 Introduction à la modélisa
Martin SchrimpfExpertise
NeuroAI, computational neuroscience, computer vision, natural language processing, human alignment, startups [CV]
Mission
Modeling the brain: Martin's research focuses on a computational understanding of the neural mechanisms underlying natural intelligence in vision and language. To achieve this goal, he bridges Deep Learning, Neuroscience, and Cognitive Science, building artificial neural network models that match the brain’s neural representations in their internal processing and are aligned to
Robert WestRobert West is a tenure-track assistant professor of computer science at EPFL, where he heads the Data Science Lab. In his research, he develops and applies techniques in machine learning, computational social science, natural language processing, social network analysis, and data mining. Bob also collaborates closely with the Wikimedia Foundation, in his role as a Wikimedia Research Fellow. Bob’s work has won several awards, including best/outstanding paper awards at ICWSM’21, ICWSM’19, and WWW’13, a best-paper runner-up award at WWW’16, a Google Faculty Research Award, a Facebook Research Award, a Hewlett-Packard Graduate Fellowship, and a Facebook Graduate Fellowship. He is actively involved in the research community, e.g., as an Associate Editor of ICWSM and EPJ Data Science and as a co-founder of the Wiki Workshop (held at WWW and ICWSM) and the Applied Machine Learning Days. Bob received his PhD in Computer Science from Stanford University, his MSc from McGill University, Canada, and his undergraduate degree from Technische Universität München, Germany.[Last updated: 25 Aug 2021]
Mats Julius StensrudEnseignement et PhD Doctorant·es actuel·les Ignacio Gonzalez Perez, Gellért Géza Perényi, Lorenzo Gasparollo, Julien David Laurendeau A dirigé les thèses EPFL de Matias Janvin, Amit Sawant Cours Causal thinking MATH-352 Ce cours donnera une présentation unifiée des méthodes modernes d'inférence causale. Nous nous concentrons sur les concepts, et nous présenterons des exemples et des idées provenant de diverses disciplines scientifiques, notamment la médecine, l'informatique, l'ingénierie,
Olga FinkEnseignement et PhD Doctorant·es actuel·les Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei A dirigé les thèses EPFL de Ismail Nejjar, Mengjie Zhao Cours Data Science for infrastructure condition monitoring CIVIL-332 Le cours couvrira les étapes pertinentes de la surveillance de l'état des infrastructures basée sur les données: l'acquisition des données, en passant p
Giancarlo Ferrari TrecateExpertise
Automatic control, Dependable control, Neural-network Control, Machine learning, Microgrids, Hybrid systems
Mission
See the webpage of the DECODE (Dependable Control and Decision) group.
Teaching & PhD PhD Students Laura Meroi, Julien Pallage, Nicolas Léo Pierre Kirsch, Simone Baratto, Daniele Martinelli, Riccardo Cescon, Jakob Nylöf, Sabri El Amrani Past EPFL PhD Students Pulkit Nahata, Mustafa Sahin Turan, Baiwei Guo, Jean-Sébastien Brouillon, Clara Galimberti, Andrea Martin, Muhammad Zakwan,
Andres Osorio SalazarExpertise
Robotics, advanced actuator design, soft actuators, sensor design, embedded systems, human-machine interface architecture, electronic-less control, mechanism design, additive and traditional manufacturing, industrial automation, process control, and fluid robotics.
Current Work
Smart Footwear for Diabetic Foot Care and Ulcer PreventionEvery 20 seconds, a person with diabetes has to face an amputation somewhere in the world. The main risk factor is high plantar pressure combined with foot nephropat
Stefana ParaschoEnseignement et PhD Doctorant·es actuel·les Jingwen Wang, Gabriel Vallat, Maxence Grangeot, Eleni Maria Skevaki, Wenqian Yang, Megi Sinani Cours Capitalizing on Uncertainty AR-809 Digital design and making: A critical introduction AR-503 Le cours présente des méthodes de conception et de fabrication numériques en combinant des compétences techniques avec des connaissances théoriques et une réflexion critique. Les sujets incluent: la programmation pour la conception, la fabr
Ayberk OzkirliExpertise
Magnetic resonance imaging (MRI), visual crowding, serial dependence, population receptive field (pRF) mapping, data analysis, machine learning, age-related macular degeneration, neuroengineering, clinical neuroscience
Expertise
Magnetic resonance imaging (MRI), visual crowding, serial dependence, population receptive field (pRF) mapping, data analysis, machine learning, age-related macular degeneration, neuroengineering, clinical neuroscience
Vivek SubramanianEnseignement et PhD Doctorant·es actuel·les Giovanni Ruffolo, Giada Romano, Sanjay Manoharan, Kyle Haas, Claude Dahan, Biruktait Ayele Lemecho, Yagmur Ceren Alatas, Tugçe Delipinar A dirigé les thèses EPFL de Amin Hodaei, Mustafa Mohieldin Fadlelmula Fadlelseed A co-dirigé les thèses EPFL de Mohammad Jafarpour Cours Organic and printed electronics MICRO-505 Ce cours traite de la mise en œuvre des technologies de l'électronique organique et imprimée: les matériaux, les procédés d'impression
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.
Virginia LangVirginia started in the medical research field as a Coordinator of Research at the Clinical Research Unit Kennedy Institute of Johns Hopkins Medical Center. She was responsible for the initiation, coordination, and management and/or analysis of research projects in the Clinical Research Unit. These projects were funded by various Federal Government Agencies. Subsequent to Johns Hopkins Medical Center, Virginia entered the field of Human Factors through the doctoral program at SUNY Binghamton. Virginia held a fellowship at the Aeromedical Research Laboratory of the United States Air Force at Wright-Patterson AFB, Dayton, Ohio and a fellowship at NASA. Her research dealt with cognitive factors that differentially affect the characteristics of visual displays. Applications of this research are directly related to various medical devices and software applications providing Medical Device Human Factors by HirLan clients with 30 years of Human Factors experience. In addition, Virginia has extensive experience in the areas of product design, Customer Centered Participatory Design processes, and product lifecycle management. She is also known in the Human Computer Interaction and Usability Communities for her innovative techniques for collecting and incorporating user/customer feedback throughout the product lifecycle. In July 2014, Virginia founded and established the HirLan Institute of Human Factors with labs in Carlsbad, California and a Consortium arrangement in London, UK. HirLan supports Top Ten pharma/medical device companies, as well as, start-ups with consulting and testing services. These services are in conjunction with their clients’ FDA 510(k) and CE mark applications. Virginia holds a PhD in Cognitive-Experimental Psychology from SUNY Binghamton, and a Master of Science (ABT) in Applied Technology, Systems Science from SUNY Binghamton.
Simon HolzerHi, I am Simon Holzer. I received my B.Sc. and M.Sc. degrees in mechanical engineering with a focus on microtechnology from the Swiss Federal Institute of Technology Zurich (ETHZ) in 2020 and 2022, respectively. I am currently working towards Ph.D. in the Integrated Actuators Laboratory (LAI) at EPFL in Neuchâtel, Switzerland. My research interests lie in the field of soft robotics, artificial muscles, and biomechanics.
Sebastian Eduardo Baez LugoSebastian is a UX Researcher and Socio-Affective Neuroscientist. He holds a BSc in Experimental Psychology, an MA in Neuroscience, and a Ph.D. in Cognitive Neuroscience from the University of Geneva. His multifaceted research experience spans academia, startups, and tech companies. His primary interest lies at the crossroads of emerging technologies, human behavior, and digital health.
Yanina Yurina ShkelEnseignement et PhD Doctorant·es actuel·les Serhat Emre Coban, Anuj Kumar Yadav, Cemre Çadir Cours Advanced probability and applications COM-417 Dans ce cours, différents aspects de la théorie des probabilités sont abordés. La première partie est dévolue à ses principaux théorèmes (loi des grands nombres, théorème central limite), tandis que la seconde partie porte sur la théorie des martingales et inégalités de concentration. Signal processing COM-202 Théorie et appli.du t
