Frédéric MilaExpertise
Condensed matter theory, strongly correlated systems, frustrated and quantum magnetism, tensor networks
Mission
Perform research in condensed matter theory, whenever possible in collaboration with experimentalists at EPFL and throughout the world
Current Work
- Magnetism on the Shastry-Sutherland lattice- Tensor network approach to 2D strongly correlated systems- Thermal properties of 2D frustrated quantum magnets- Exotic phases of quantum one-dimensional models
Since 2003 Full Professor at EPFL (
Thomas MountfordTeaching & PhD Past EPFL PhD Students Damien Gauthier, Samir Brahim Belhaouari, Driss Baraka, Daniel Rodrigues Valesin, Samuel Schöpfer, Kamran Kalbasi, Jacques Saliba, Hao Xue, Keming Chen Past EPFL PhD Students as codirector Guillaume Charles Woessner Courses Analysis I MATH-101(d) Study the fundamental concepts of analysis, and the differential and integral calculus of real-valued functions of one real variable. Markov chains MATH-332 The course follows the text of Norris
Giuseppe CarleoGiuseppe Carleo is a computational quantum physicist, whose main focus is the development of advanced numerical algorithms tostudy challenging problems involving strongly interacting quantum systems.He is best known for the introduction of machine learning techniques to study both equilibrium and dynamical properties,based on a neural-network representations of quantum states, as well for the time-dependent variational Monte Carlo method.He earned a Ph.D. in Condensed Matter Theory from the International School for Advanced Studies (SISSA) in Italy in 2011.He held postdoctoral positions at the Institut d’Optique in France and ETH Zurich in Switzerland, where he alsoserved as a lecturer in computational quantum physics.In 2018, he joined the Flatiron Institute in New York City in 2018 at the Center for Computational Quantum Physics (CCQ), working as a Research Scientist and project leader, and also leading the development of the open-source project NetKet.Since September 2020 he is an assistant professor at EPFL, in Switzerland, leading the Computational Quantum Science Laboratory (CQSL).
Elisabeth AgoritsasExpertise
=> See my personal homepage for more content https://eagoritsas.wordpress.com.Statistical physics of classical disordered systems, with focus on specific classes of models:disordered elastic interfaces and random manifolds,mesoscopic elasto-plastic models (spatially-resolved and effectively mean-field versions),mean-field description of structurally disordered systems (e.g. glasses) in infinite dimensions,continuous random perceptron model.1D Kardar-Parisi-Zhang equation and its encompassing unive Martin HairerTeaching & PhD PhD Students Colin Piernot, Wenhao Zhao, Declan Rellan Stacy Courses Advanced stochastic analysis MATH-525 This course will give you in-depth knowledge in some topics of modern stochastic analysis. We will start with a general introduction to Gaussian measure theory followed by an introduction to Malliavin calculus and a selection of advanced topics.
Awards Fermat Prize Institut de Mathématiques de Toulouse 2013 Fields Medal IMU 2014 Honorary doctorate in science Hong Kong
Clément Hongler2006: B.Sc. Math, EPFL2008: M.Sc. Math, EPFL2010: Ph.D. Math, Université de Genève2010-2014: Ritt Assistant Professor, Columbia University2014-2018 Tenure-Track Assistant Professor, EPFL2019-present: Associate Professor, EPFL
Olivier MartinOlivier J.F. Martin received the M.Sc. and Ph.D. degrees in physics in 1989 and 1994, respectively, from the Swiss Federal Institute of Technology, Lausanne (EPFL), Switzerland. In 1989, he joined IBM Zurich Research Laboratory, where he investigated thermal and optical properties of semiconductor laser diodes. Between 1994 and 1997 he was a research staff member at the Swiss Federal Institute of Technology, Zurich (ETHZ). In 1997 he received a Lecturer fellowship from the Swiss National Science Foundation (SNSF). During the period 1996-1999, he spent a year and a half in the U.S.A., as invited scientist at the University of California in San Diego (UCSD). In 2001 he received a Professorship grant from the SNSF and became Professor of Nano-Optics at the ETHZ. In 2003, he was appointed Professor of Nanophotonics and Optical Signal Processing at the Swiss Federal Institute of Technology, Lausanne (EPFL), where he is currently head of the Nanophotonics and Metrology Laboratory and Director of the Microengineering Section.
Loïc Jean Pierre HerviouTeaching & PhD Courses Solid state physics III PHYS-419 The aim of this course is to provide an introduction to the theory of a few remarkable phenomena of modern condensed matter physics ranging from the quantum Hall effects to superconductivity.
Nicolas MacrisNicolas Macris received the PhD degree in theoretical physics from EPFL and then pursued his scientific activity at the mathematics department of Rutgers University (NJ, USA). He then joined the Faculty of Basic Science of EPFL, working in the field of quantum statistical mechanics and mathematical aspects of the quantum Hall effect. Since 2005 he is with the Communication Theories Laboratory and Information Processing group of the School of Communication and Computer Science and currently works at the interface of statistical mechanics, information theory and error correcting codes, inference and learning theory. He held long-term visiting appointments and collaborations with the University College and the Institute of Advanced studies in Dublin, the Ecole Normale Supérieure de Lyon, the Centre de Physique Theorique Luminy Marseille, Paris XI Orsay, the ETH Zürich and more recently Los Alamos National Lab. CV and publication list.
Rüdiger UrbankeRüdiger L. Urbanke obtained his Dipl. Ing. degree from the Vienna University of Technology, Austria in 1990 and the M.Sc. and PhD degrees in Electrical Engineering from Washington University in St. Louis, MO, in 1992 and 1995, respectively. He held a position at the Mathematics of Communications Department at Bell Labs from 1995 till 1999 before becoming a faculty member at the School of Computer & Communication Sciences (I&C) of EPFL. He is a member of the Information Processing Group. He is principally interested in the analysis and design of iterative coding schemes, which allow reliable transmission close to theoretical limits at low complexities. Such schemes are part of most modern communications standards, including wireless transmission, optical communication and hard disk storage. More broadly, his research focuses on the analysis of graphical models and the application of methods from statistical physics to problems in communications. From 2000-2004 he was an Associate Editor of the IEEE Transactions on Information Theory and he is currently on the board of the series "Foundations and Trends in Communications and Information Theory." In 2017 he was President of the Information Theory Society. From 2009 till 2012 he was the head of the I&C doctoral school, in 2013 he served as Dean a. i. of I&C, and since 2016 he is the Associated Dean for teaching of I&C. He is a co-author of the book "Modern Coding Theory" published by Cambridge University Press. Awards: 2021 IEEE Information Theory Society Paper Award 2016 STOC Best Paper Award 2014 La Polysphere Teaching Award 2014 IEEE Hamming Medal 2013 IEEE Information Theory Society Paper Award 2011 MASCO Best Paper Award 2011 IEEE Koji Kobayashi Award 2009 La Polysphere Teaching Award 2002 IEEE Information Theory Society Paper Award Fulbright Scholarship My students have won the following awards: M. Mondelli, 2021 IEEE Information Theory Paper Award M. Mondelli, EPFL Doctorate Award 2018 M. Mondelli, Patrick Denantes Award, 2017 M. Mondelli, IEEE IT Society Student Paper Award at ISIT, 2015 M. Mondelli, Dan David Prize Scholarship, 2015 H. Hassani, Inaugural Thomas Cover Dissertation Award, 2014 S. Kudekar, 2013 & 2021 IEEE Information Theory Paper Award A. Karbasi, Patrick Denantes Award, 2013 V. Venkatesan, Best Paper Award at MASCOTS, 2011 A. Karbasi, Best Student Paper Award at ICASSP, 2011 (with R. Parhizkar) A. Karbasi, Best Student Paper Award at ACM SIGMETRICS, 2010 (with S. Oh) S. Korada, ABB Dissertation Award, 2010 S. Korada, IEEE IT Society Student Paper Award at ISIT, 2009 (with E. Sasoglu) S. Korada, IEEE IT Society Student Paper Award at ISIT, 2008
Mikhail ChapochnikovMikhail Shaposhnikov was born in Sochi, Russia, in 1956. He got his degree from Moscow States University in 1979 and his PhD from the Institute for Nuclear Research of the Russian Academy of Sciences in 1982 for his work on the problem of baryon asymmetry of the universe in grand unified theories. He worked from 1982 till 1986 as a junior research scientist and from 1986 till 1991 as a senior research scientist at the Theory Division of the Institute for Nuclear Research of the Russian Academy of Sciences (Moscow). From 1991 till 1998 he worked as a staff member at the Theory Division of European Organisation for Nuclear Research (CERN, Geneva). In 1998 he was appointed as a Professor of Theoretical Physics at the University of Lausanne, in 1999 he became a Director of the Institute of Theoretical Physics of Lausanne University. Since October 2003 he is a Professor at EPFL, leading the Laboratory for Particle Physics and Cosmology.
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.
