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
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.
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,
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
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.
Elena PerazziEnseignement et PhD Cours Advanced derivatives FIN-503 Le cours couvre une série de sujets avancés dans le domaine de l'évaluation des produits dérivés. Game theory and strategic decisions MGT-300 La theorie des jeux étudie les interactions strategiques entre des agents rationnels. Elle a une myriade d'applications dans la politique, les affaires, le sport. Une de ses branches est la theorie des enchères, qui a guidé le développement d' Ebay, des enchères Google et du sprec
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
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
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.
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
Nicolas Henri Bernard FlammarionNicolas Flammarion is a tenure-track assistant professor in computer science at EPFL. Prior to that, he was a postdoctoral fellow at UC Berkeley, hosted by Michael I. Jordan. He received his PhD in 2017 from Ecole Normale Superieure in Paris, where he was advised by Alexandre d’Aspremont and Francis Bach. In 2018 he received the prize of the Fondation Mathematique Jacques Hadamard for the best PhD thesis in the field of optimization. His research focuses primarily on learning problems at the interface of machine learning, statistics and optimization.
Felipe Osiel Hernández CastroExpertise
My research interests lie mainly in Ergodic Theory, Arithmetic combinatorics, Ramsey Theory, and Multiplicative Number Theory.
Please visit my professional webpage for more information. Curriculum vitae CV
Teaching & PhDTeaching & PhD Teaching Assistant for the course Ergodic theory (Autumn semester 2023)Teaching Assistant for the course Discrete mathematics (Spring semester, 2024)Teaching Assistant for the course Measure and integration (Fall semester, 2024)Teaching Assistant for the course Disc
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
Xue-Mei Li-HairerEnseignement et PhD Doctorant·es actuel·les Johann Williams, Timon Miehling, Szymon Sobczak, Kexing Ying Cours Introduction to multi-scale stochastic dynamics MATH-487 Ce cours présente les systèmes lents/rapides et les outils mathématiques permettant de dériver des équations efficaces régissant leur comportement. Les étudiants acquerront les concepts et techniques fondamentaux pour analyser rigoureusement les systèmes stochastiques multi-échelles complexes
Pawel DuchExpertise
My present research focuses on the intersection between probability theory, PDE theory and Euclidean quantum field theory. I am especially interested in problems involving singular stochastic partial differential equations and renormalization. I have also a background in mathematical aspects of perturbative and axiomatic quantum field theory as well as general relativity.
I am a postdoctoral researcher in the group of Martin Hairer. Previously, I was a postdoc at Adam Mickiewicz University in Pozn
Giuseppe CarleoTwitter
https://twitter.com/gppcarleo
Enseignement et PhD Doctorant·es actuel·les Gian Gentinetta, Linda Mauron, Samuele Piccinelli, Alessandro Sinibaldi, Shao Hen Chiew, David Linteau, Clemens Giuliani, Ali Goodarzi, Gianluca Grosso, Ruize Ma, Ekaterina Pankovets A dirigé les thèses EPFL de Dian Wu, Julien Sebastian Gacon, Gabriel Maria Pescia, Barison Stefano, Imelda Romero Cours Advanced computational physics PHYS-339 Le cours couvre l'algèbre linéaire dense/creuse, les méthodes variati Sayan BiswasExpertise
Decentralized Learning; Federated Learning; Ethical ML focusing on Privacy, Fairness, and Personalization; Location Privacy.
I am a Postdoctoral Researcher at the SaCS lab at EPFL. I completed my PhD in Computer Science from INRIA and école Polytechnique in France, under the supervision of Catuscia Palamidessi. Previously, I have been a Visiting Scholar at the School of Computing at Macquarie University in Sydney, Australia, collaborating with Annabelle McIiver and Natasha Fernandes, and at WMG, t
