Georgios MoschidisTeaching & PhD PhD Students Abraham Gabriel Dorsaz Courses Analysis IV (for EL, GM, MX) MATH-207(c) This course serves as an introduction to the theory of complex analysis, Fourier series and Fourier transforms, the Laplace transform, with applications to the theory of ordinary and partial differential equations. These tools play an integral role in most branches of science and engineering. Differential geometry I - curves and surfaces MATH-213 This course serves as an intr
Xavier Fernandez-Real GironaTeaching & PhD PhD Students Roberto Colombo Courses Optimal transport MATH-476 The first part is devoted to Monge and Kantorovitch problems, discussing the existence and the properties of the optimal plan. The second part introduces the Wasserstein distance on measures and develops applications of optimal transport to PDEs, functional/geometric inequalities, traffic models.
Florian Karl RichterCurriculum vitae You can download my CV here
ResearchResearch Fields Ergodic Theory, Combinatorics, Number TheoryList of Publications Open-access preprints and e-prints of all my publications are freely available on arXiv ↗ .An inverse theorem for sumsets of sets of positive density in the integersEthan Ackelsberg, Florian K. Richter submitted, 117 pageslink ↗Weighted averages of arithmetic functions and applications to equidistributionVitaly Bergelson, Michael Reilly, Florian K. Richter submitted, 29 page
Leonid MoninTeaching & PhD Courses Algebra III - rings and fields MATH-215 This is an introductory course in ring and field theory. Analysis I (English) MATH-101(en) We study the fundamental concepts of analysis, calculus and the integral of real-valued functions of a real variable. Topology III - Homology MATH-323 Homology is one of the most important tools to study topological spaces and it plays an important role in many fields of mathematics. The aim of this course is
Younes Pierre ZineExpertise
I mainly work on (deterministic and random) nonlinear PDEs by using techniques and insights from PDE theory, probability theory and Fourier analysis.My website:https://younes-zine.github.io
Expertise
I mainly work on (deterministic and random) nonlinear PDEs by using techniques and insights from PDE theory, probability theory and Fourier analysis.My website:https://younes-zine.github.io
Education Ph.D. | 2020 – 2023 The University of Edinburgh 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
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
Sofia Charlotta OlhedeI am a professor of Statistics at EPFL. I did my PhD in Mathematics at Imperial College London, and graduated in 2003. I was an assistant professor (lecturer) at Imperial College London 2002-2006, and an associate professor (senior lecturer) 2006-2007. In 2007 I moved to University College London and became a full professor. I moved to EPFL in 2019, and in 2018 I became an Institute of Mathematical Statistics Fellow with citation “For seminal contributions to the theory and application of large and heteroge
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.
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 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
Lénaïc ChizatTeaching & PhD PhD Students Javier Esteban Maass Martinez Past EPFL PhD Students Guillaume Yitian Wang Courses Computational optimal transport MATH-528 Computational aspects of measure transportation, from classical optimal transport to modern denoising diffusion models. Topics in machine learning MATH-520 Mathematical analysis of modern supervised machine learning techniques, with an emphasis on the mathematics of artificial neural networks.
Mats Julius StensrudTeaching & PhD PhD Students Ignacio Gonzalez Perez, Gellért Géza Perényi, Lorenzo Gasparollo, Julien David Laurendeau Past EPFL PhD Students Matias Janvin, Amit Sawant Courses Causal thinking MATH-352 This course will give a unified presentation of modern methods for causal inference. We focus on concepts, and we will present examples and ideas from various scientific disciplines, including medicine, computer science, engineering, economics and epidemiology. Probability and statistics (
Yanina Yurina ShkelTeaching & PhD PhD Students Serhat Emre Coban, Anuj Kumar Yadav, Cemre Çadir Courses Advanced probability and applications COM-417 In this course, various aspects of probability theory are considered. The first part covers the main theorems in the field (law of large numbers, central limit theorem), while the second part focuses on the theory of martingales and concentration inequalities. Signal processing COM-202 Signal processing theory and applications: discrete and cont
Olga FinkTeaching & PhD PhD Students Han Sun, Leandro Von Krannichfeldt, Keivan Faghih Niresi, Zepeng Zhang, Vinay Sharma, Chenghao Xu, Raffael Pascal Theiler, Kevin Antonio Steiner, Sergei Garmaev, Amaury Wei Past EPFL PhD Students Ismail Nejjar, Mengjie Zhao Courses Data Science for infrastructure condition monitoring CIVIL-332 The course will cover the relevant steps of data-driven infrastructure condition monitoring, starting from data acquisition, going through the steps pre-processing of real
Emmanuelle Brigitte Marie DavidMission
After six years leading the EPFL Space Center — spanning teaching, student associations, research, and innovation — I have a grounded understanding of what makes EPFL exceptional and where it faces real complexity. I want to bring that perspective into institutional governance.Constructive by nature. I am solution-oriented, genuinely enjoy working across large and diverse stakeholder groups, and know how to navigate the constraints of a complex organization while keeping things moving forward.A brid
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).
