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.
Kumar Varoon AgrawalEnseignement et PhD Doctorant·es actuel·les Fabian Yuki Scheffler, Archisman Ghosh, Shaoyu Wang, Amin Bouzaiene, Shuqing Song, Anu Pulparambil, Ceren Kocaman, Moein Fazli Mamaghani, Stefania Bempeli, Yueqing Shen, Daniele Micucci, Samson Xavier Robbins, Mahesh Manikantan Sandhya A dirigé les thèses EPFL de Shiqi Huang, Mojtaba Chevalier, Mostapha Dakhchoune, Wan-Chi Lee, Mohammad Tohidivahdat, Shaoxian Li, Heng-Yu Chi, Kuang-Jung Hsu, Luc Sébastien Bondaz Cours Chemical engineering product design
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.
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
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]
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 Anne-Florence Raphaëlle BitbolI was trained in physics, and always had a strong interest in biology. I am broadly interested in understanding biological phenomena in a quantitative way, through physical concepts and mathematical and computational tools. I investigate the relative impacts of optimization and historical contingency in biological evolution, both at the scale of protein sequences and at the scale of microbial populations.Here is my research group website.Curriculum vitae Here is my complete CV. Professional experience:Since
Athanasios NenesEnseignement et PhD Doctorant·es actuel·les Berkay Dönmez, Ernest Abboud A dirigé les thèses EPFL de Paraskevi Georgakaki, Lucile Ricard Cours Atmospheric processes: from cloud to global scales ENV-407 L'objectif principal est de voir les processus atmosphériques les plus importants de l'échelle locale à l'échelle globale. Le cours démarrera avec les processus nuageux, continuera avec les phénomènes synoptiques comme les cyclones extratropicaux et fronts, pour finir par la modélisation num
Iurii TimrovProfessional employment
Postdoctoral researcherFebruary 2016 - presentAdvisor: Prof. Nicola MarzariPlace: STI IMX THEOS, Ecole Polytechnique Federale de Lausanne (Lausanne, Switzerland)Postdoctoral researcherJuly 2013 - January 2016Advisor: Prof. Stefano BaroniPlace: Condensed Matter Sector, Scuola Internazionale Superiore di Studi Avanzati (Trieste, Italy)Postdoctoral researcherApril 2013 - June 2013Advisor: Dr. Nathalie VastPlace: Laboratoire des Solides Irradies, Ecole Polytechnique (Palaiseau, France)
Education
PhDSeptember 2009 - March 2013Advisor: Dr. Nathalie Vast Place: Laboratoire des Solides Irradi'es, Ecole Polytechnique (Palaiseau, FranceTitle: Ab initio study of plasmons and electron-phonon coupling in bismuth: from free-carrier absorption towards a new method for electron energy-loss spectroscopyDate of defense: 27.03.2013Honors: PhD degree in physics with honors ("Tres honorable")Master in PhysicsSeptember 2008 - June 2009Place: Department of Theoretical Physics, National Taras Shevchenko University of Kyiv (Kyiv, Ukraine)Honors: Master's degree with honorsBachelor in PhysicsSeptember 2004 - June 2008Place: Department of Theoretical Physics, National Taras Shevchenko University of Kyiv (Kyiv, Ukraine)Honors: Bachelor's degree with honorsHigh School StudiesSeptember 1994 - June 2004Place: Collegium 11 (Chernigov, Ukraine)Honors: Honors degree with a Gold medal
Pasquale ScarlinoI obtained my master's degree in Physics at the University of Salento, Lecce (Italy) in February 2011. During 2006-2011, I have also been a student of Scuola Superiore ISUFI (SSI). SSI is one of six schools of excellence established in Italy to develop the intellectual capital in technological and social sciences. I conducted an external Master thesis project during an 8 months internship in the Quantum Transport Group at TU Delft, under the supervision of Prof. L.M.K. Vandersypen. There, I implemented the Quantum Point Contact Radio-Frequency Reflectometry technique, which allows increasing the single-shot electron spin readout bandwidth and is currently routinely used in the group.I obtained my Ph.D. degree in February 2016, in the Spin Qubits group of Prof. L.M.K. Vandersypen at the Kavli Institute of Nanoscience-Qutech (TU Delft). During my Ph.D. I have been leading the Si/SiGe spin qubits project, collaborating with the M. Eriksson Group at Wisconsin University. In parallel, I have been working on other different projects, in particular with GaAs depletion quantum dots, high impedance superconducting resonators, and surface acoustic wave resonators. I have been working as a Postdoc fellow in the group of Prof. A. Wallraff (Quantum Device Lab) at ETH Zurich. My main project, in collaboration with the group of Prof. K. Ensslin and Prof. T. Ihn, consisted in integrating semiconductor and superconductor technologies. Realizing a well-controlled interface between the semiconductor and superconductor-based quantum information technologies may allow harnessing the best of both device architectures, for example by providing an interface between strongly coupled charge state and high coherence spin states. Furthermore, it enables the possibility to explore light/matter hybridization in a class of solid-state systems and regimes that are new in the context of quantum optics.From June 2019 till September 2020, I have been a Senior Researcher at Microsoft Station Q Copenhagen and at the Center for Quantum Devices in Copenhagen, focusing on developing semiconductor-superconducting hybrid hardware for topologically protected quantum computation.Since October 2020, I am a tenure track Assistant Professor of Physics in the School of Basic Sciences at the EPFL where I founded the Hybrid Quantum Circuit (HQC) laboratory.
Pablo Antolin SanchezEnseignement et PhD Doctorant·es actuel·les Philipp Christoph Weder, Davor Dobrota A co-dirigé les thèses EPFL de Ondine Chanon Cours Analysis III MATH-202(c) Le cours étudie les concepts fondamentaux de l'analyse vectorielle et de l'analyse de Fourier-Laplace en vue de leur utilisation pour résoudre des problèmes pluridisciplinaires d'ingénierie scientifique. Analysis III (for IC) MATH-203(d) Le cours étudie les concepts fondamentaux de l'analyse vectorielle et de l'analys
Daniel Alexander Florez OrregoEnseignement et PhD Doctorant·es actuel·les Vibhu Baibhav Cours Advanced energetics ME-451 Méthodes pour l'utilisation rationnelle et la conversion de l'énergie dans les processus industriels: comment analyser l'utilisation de l'énergie, calculer la récupération de chaleur par analyse de pincement, définir le réseau d'échangeurs thermiques et réaliser une analyse exergétique.
Raffaella BuonsantiEnseignement et PhD Doctorant·es actuel·les Riya Gupta, Jennifer Calderon Mora, Coline Boulanger, Moritz Tritschler, Marco Fabbiano, Seyedmohamadjavad Chabok, Hugh Andrew Warkentin A dirigé les thèses EPFL de Chethana Janardhana Gadiyar, Seryio Saris, Valeria Mantella, Seyedehbehnaz Varandili, Pranit Srinivas Iyengar, Yannick Thomas Guntern, Jan Vávra, Laia Castilla Amorós, Valery Okatenko, Ona Segura Lecina, Ludovic Emile Frédy Zaza, Petru Pasquale Albertini Cours Introduction au génie chimique et à l'
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.
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
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.
Annalisa BuffaEnseignement et PhD Doctorant·es actuel·les Gonzalo Bonilla Moreno, Philipp Christoph Weder, Yannis Dirk Voet, Fabio Marcinno, Ferhat Sindy, Francesco Sala, Markus Renoldner, Mohamed Ben Abdelouahab, Davor Dobrota A dirigé les thèses EPFL de Luca Coradello, Ondine Chanon, Riccardo Puppi Cours Numerical approximation of PDEs MATH-451 Ce cours porte sur la dérivation, l'analyse théorique et l'implémentation de la méthode des éléments finis pour l'approximation numérique des équations aux dér
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,
