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 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
Laura GrigoriExpertise
Numerical linear algebra, deterministic and randomized algorithmsHigh performance computing for scientific applicationsHigh dimensional problems and tensor computationsApplications in astrophysics, molecular simulations, etcCombinatorial scientific computingMathematical Software
Teaching & PhD PhD Students Israa Fakih, Zhipeng Xue, Andrea Di Antonio, Mariana Graciela Martinez Aguilar, Guifré Sánchez i Serra Courses Numerical analysis and computational mathematics MATH-456 The cou
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
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
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
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
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.
Parmenion MavrikakisExpertise
Computational electromagnetics, integral equations, finite element analysis, metasurfaces, photonics, plasmonics and microwaves.
Current Work
Developing a C++ code for the modeling of light scattering in layered media with the surface integral equation method.
I am a PhD student in the Electrical Engineering Department (EDEE) at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Nanophotonics and Metrology Laboratory (NAM), part of the Microengineering Department (IEM) at EPFL. M
Myrto LimniosTeaching & PhD Courses Empirical processes MATH-522 We learn how to control the nonasymptotic and random behavior of collections of estimators, when indexed by classes of functions/sets. Examples range from prototypical estimators used by statisticians, to nonparametric models used in machine learning. Regression methods MATH-408 General graduate course on regression methods
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 (
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
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
Michael HerbstExpertise
For more information about our research, see https://matmat.org/research/.
Teaching & PhD PhD Students Niklas Frederik Schmitz, Anna Paulish, Bruno Ploumhans, Benedikt Menges Courses Error control in scientific modelling MATH-500 Errors are ubiquitous in computational science as neither models nor numerical techniques are perfect. With respect to eigenvalue problems motivated from materials science and atomistic modelling we discuss, implement and apply numerical techniques for e Andrés Ignacio Cristi EspinosaExpertise
- Online Algorithms & Sequential Decision-Making- Algorithmic Game Theory- Mechanism & Market Design
Teaching & PhD PhD Students Jiechen Zhang, Aruzhan Amanbayeva Courses Algorithmic game theory MGT-435 We will study mathematical models of the interplay between algorithms and strategic behavior. We cover fundamental concepts from game theory and mechanism design, including Nash equilibria, the price of anarchy, auctions and market design, incentive compatibility, and online learn
Leonardo Vincenzo SantoroResearch interests:
I am interested in statistical inference for random processes and inverse problems arising in the context of optimal transport and functional data analysis. Currently, my work is focusing on kernel methods in theoretical machine learning.
Education Master's Degree | Mathematics 2018 – 2020 ETH (Zürich) Bachelor's Degree | Mathematics 2015 – 2018 UNITN (Trento)
Yuning JiangExpertise
Learning- and optimization- based policies for operating complex intelligent systems such as nonlinear autonomous systems (e.g., au- tonomous vehicles, robotics, and smart buildings) and large-scale multi-agent systems (e.g., power and energy systems, IoT and traffic networks).
Expertise
Learning- and optimization- based policies for operating complex intelligent systems such as nonlinear autonomous systems (e.g., au- tonomous vehicles, robotics, and smart buildings) and large-scale multi-agent sy
