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]
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
Geovani RizkExpertise
Distributed Machine Learning, Robustness, Safety, Optimization, Multi-Agent, Bandits in Graphs
I am a postdoctoral researcher at école Polytechnique Fédérale de Lausanne since 2022, where I work with Rachid Guerraoui on robustness of distributed machine learning algorithms. From 2018 to 2022, I completed my Ph.D. in computer science at Université Paris Dauphine-PSL on multi-agent bandits in graphs under the supervision of Yann Chevaleyre, Rida Laraki, Igor Colin, and Albert Thomas.Pre-prints Over
Lenka ZdeborováLenka Zdeborová is a Professor of Physics and of Computer Science in École Polytechnique Fédérale de Lausanne where she leads the Statistical Physics of Computation Laboratory. She received a PhD in physics from University Paris-Sud and from Charles University in Prague in 2008. She spent two years in the Los Alamos National Laboratory as the Director's Postdoctoral Fellow. Between 2010 and 2020 she was a researcher at CNRS working in the Institute of Theoretical Physics in CEA Saclay, France. In 2014, she was awarded the CNRS bronze medal, in 2016 Philippe Meyer prize in theoretical physics and an ERC Starting Grant, in 2018 the Irène Joliot-Curie prize, in 2021 the Gibbs lectureship of AMS. She is an editorial board member for Journal of Physics A, Physical Review E, Physical Review X, SIMODS, Machine Learning: Science and Technology, and Information and Inference. Lenka's expertise is in applications of concepts from statistical physics, such as advanced mean field methods, replica method and related message-passing algorithms, to problems in machine learning, signal processing, inference and optimization. She enjoys erasing the boundaries between theoretical physics, mathematics and computer science.
Martin JaggiMartin Jaggi is a Tenure Track Assistant Professor at EPFL, heading the Machine Learning and Optimization Laboratory. Before that, he was a post-doctoral researcher at ETH Zurich, at the Simons Institute in Berkeley, and at École Polytechnique in Paris. He has earned his PhD in Machine Learning and Optimization from ETH Zurich in 2011, and a MSc in Mathematics also from ETH Zurich.
Benjamin Alexander Kellenberger2020–: Postdoctoral Researcher, EPFL, Sion, Switzerland2020: Postdoctoral researcher, Wageningen University, Netherlands2017–2020: PhD (cont'd); Wageningen University, Netherlands2016–2017: PhD; University of Zurich, Switzerland2009–2014: BSc. and MSc. in geography (remote sensing and GIS) and computer science; University of Zurich, Switzerland
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
Vittorio ErbaEnseignement et PhD Cours Statistical physics of computation PHYS-512 Les étudiants comprennent les outils de la physique statistique des systèmes désordonnés et les appliquent pour étudier des problèmes d'informatique et de statistiques en théorie des graphes, en optimisation discrète, ainsi qu'en inférence et en apprentissage automatique.
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,
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
Lénaïc ChizatEnseignement et PhD Doctorant·es actuel·les Javier Esteban Maass Martinez A dirigé les thèses EPFL de Guillaume Yitian Wang Cours Computational optimal transport MATH-528 Aspects computationnels de la théorie du transport de mesures, du problème classique du transport optimal classique au modèles de diffusion modernes. Topics in machine learning MATH-520 Analyse mathématique des techniques modernes d'apprentissage supervisé, avec une emphase sur les réseaux de neurones arti
Myrto LimniosExpertise
Nonparametric statistics, statistical learning theory and methods, stochastic processes
Enseignement et PhD Cours Empirical processes MATH-522 Nous étudierons comment contrôler le comportement non-asymptotique et aléatoire de collections d'estimateurs, lorsqu'indexées par des classes de fonctions/d'ensembles. Des exemples en statistiques et des méthodes non-paramétriques en apprentissage automatique seront traités. Regression methods MATH-408 Cours de niveau master
Akuto Akpedze KonouAkuto Akpedze KONOU AKA Rolande est une jeune femme du Togo (Afrique de l'Ouest), architecte et urbaniste assermentée, communicatrice, auteur et motivatrice de talent. Elle est passionnée par la recherche en matière de développement durable, d'entrepreneuriat et de technologies vertes. Akuto est actuellement doctorante au laboratoire CEAT/EPFL et travaille sur un volet de recherche du projet Sinergia du FNS "Contributions africaines à la santé mondiale": "Circulation des connaissances et des innovations" (https://globalhealthafrica.ch/). Le projet de recherche étudie les connaissances et les pratiques liées à l'amélioration de la santé et des soins de santé qui ont été développées ou conçues en Afrique. Le projet est mené par une équipe pluridisciplinaire de l'EPFL, de l'Université de Bâle et du Swiss TPH. Fulbright et DKG World Fellow, Akuto a étudié au département de planification communautaire et régionale (College of Design) de l'Université d'État de l'Iowa aux États-Unis en tant qu'assistante de recherche, ainsi qu'après un master en architecture et en urbanisme à l'EAMAU.Akpedze pratique son métier depuis 7 ans, en intégrant au mieux les principes de l'architecture et de l'urbanisme durables. Après son master à l'EAMAU, GIGA, le groupe Eric DUVAL, l'OIF, GIZ, R-SUD, le gouvernement togolais de la prospective et de l'évaluation des politiques publiques, UN-Habitat, le PNUD, le groupe GFA et la Banque mondiale ont renforcé ses compétences. Elle s'engage à travers son domaine à contribuer à la protection de la planète et à la bonne santé de ses habitants. Akpedze soutient que tout être vivant a droit à un environnement sain et décent, et son objectif est d'utiliser l'architecture sociale et l'aménagement durable du territoire pour soutenir les communautés. Akpedze est active au sein d'associations professionnelles telles que l'ONAT, l'OSM, Minodoo, YALI Allumni, TDIF Think Tank et a participé de manière dynamique à plusieurs ateliers internationaux, concours, expositions, puis conférences et formations à l'entrepreneuriat ou au leadership, et sur les questions de villes intelligentes. Co-fondateur de AXE DURABLE et AfriK Durabiliterre, Akuto Akpedze KONOU est convaincue d'avoir une contribution unique à la R & D dans le domaine de la planification durable pour un impact positif sur le Sud et le développement mondial. 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,
Baraka Jean-Claude MunyakaExpertise
Transport modelling, Logistics, Supply Chain Systems, and Urban Planning, Geospatial Analysis, Lean Manufacturing
Dr. Jean-Claude Munyaka Baraka is a Research Collaborator at the Urban and Regional Planning Community (CEAT) at the Swiss Federal Institute of Technology in Lausanne (EPFL). A citizen of the Democratic Republic of Congo, Dr. Munyaka holds a Doctorate in Industrial and Systems Engineering from the University of Pretoria, South Africa, and earned his Master's degree with Cum Laude in th
Federico AmatoI have an MSc in Engineering and a Ph.D. in Sustainable Development and Innovation Engineering. After a three-year Postdoc in Environmental Data Mining, in 2021 I joined the Swiss Data Science Centre, a joint venture between the polytechnical schools of Lausanne (EPFL) and Zurich (ETH) having as mission the acceleration of the digital transformation of the academic community and the industrial sector, putting to work Artificial Intelligence and Machine Learning and facilitating the multidisciplinary exchange of data and knowledge.
Over the years I worked on the development of methodological tools to mine and model big spatiotemporal datasets. I extensively applied such methods to study the interaction between the spatial and temporal components of environmental and geographical phenomena, and their consequences in terms of spatial planning and urban geography. My academic activity has focused on the analysis of land-use dynamics and their relationship with climate, pollution, natural hazards, and other social/economic phenomena. I have deep competencies in applied statistics, machine learning, geocomputation, spatial statistics, urban modeling, and remote sensing. I am also an expert in European Project development and implementation.
Mandresy Ivan Ny HanitraIvan received in 2013 a bachelor degree in Physics and Chemistry from Grenoble Institute of Technology (France), after two years of intensive training at Lycée Pierre de Fermat (France). He currently holds a master degree in Micro and Nanotechnologies for Integrated Systems, a joint degree between Politecnico di Torino (Italy), Grenoble Institute of Technology (France), and EPFL. During this international training, he acquired knowledge in Semiconductor physics and technology, Microtechnology (cleanroom practice), Microelectronics (analog/digital circuits design), Nanoelectronics (state-of-the art of emerging electron devices), Micro-nano systems modelling, VLSI design and testing, Embedded systems, and Optoelectronics. He pursued his master thesis at EPFL, in Electronics Laboratory (Prof. Kayal), developing low-power systems for photoplethysmographic-based heart rate monitoring. Ivan joined the Integrated Systems Laboratory (Prof. De Micheli), in October 2016, where he designed and realized in cleanroom multi-sensing platforms for electrochemical sensing applications.
