Simon BossoneyTeaching & PhD Courses Algèbre linéaire et géométrie (pour MAN) PREPA-032(a) We present the fundamental notions of linear algebra in the geometric context where they emerged. We will therefore emphasize the dimensions 2 and 3, and insist on the visualisation of classical objects and operations in the plane and in the 3D space. Analysis I (for CMS) PREPA-003(a) This first semester class is an introduction to the basis of differential calculus. Analysis II (for CMS)
Giordano FaviExpertise
Research: Non associative Algebra, Category Theory, Triangulated Category Theory, Balmer-Witt Theory, Quadratic Forms in Characteristic 2, Galois Theory, Essential dimension, Tensor Triangular GeometryTeaching: Algebra (Associative, Linear, Commutative or not), Differential Calculus , Algebraic Geometry/Topology, etc.
Current work
Teaching: My current work at EPFL is half time dedicated to teaching mathematics for 1st year students. It is very important to give satisfactory introductory courses
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
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
Sixuan Sven WangTeaching & PhD PhD Students Leonardo Nevali Courses Bayesian statistics MATH-339 A first introduction to Bayesian statistics, assuming knowledge from first courses in statistics and probability. We will focus on foundational statistical and mathematical aspects such as the decision theoretic background, consistency for large sample sizes, and algorithms for Bayesian computation.
Philippe MüllhauptExpertise
Nonlinear Control (Geometry and Algebra)Classical DynamicsRoboticsStatistics
Mission
Provide rigorous technical and scientific training in nonlinear control, classical mechanics, and statistical theory
Current Work
Research and teaching in the fields of control theory, statistics, dynamical systems, and general mechanics.
Philippe Mullhaupt received his Diplôme d Education Ing�nieur | Electricit� 1993 – 1993 EPFL DEA | Automatique et Traitement du Signal 199
Roger HerschRoger D. Hersch is professor of Computer Science and head of the Peripheral Systems Laboratory at EPFL. He received his engineering degree from ETHZ in 1975, worked in industry from 1975 to 1980, and obtained his PhD degree from EPFL in 1985. He directed the widely known
Visible Human Web Server project
, which offers a number of services for the visualization of human anatomy.
His current research focuses on color reproduction, spectral color prediction models, moiré imaging, and visual document security. Recent achievements include the PhotoProtect technology, which incorporates text as chromatic differences in order to protect identity photographs (Swiss driving license), microstructure imaging, which is used by railways companies (SNCF, RENFE) and festival organizers (Paleo) to print tickets at home and the band moire imaging technology for the protection of security documents.
Annalisa BuffaTeaching & PhD PhD Students Gonzalo Bonilla Moreno, Philipp Christoph Weder, Yannis Dirk Voet, Fabio Marcinno, Ferhat Sindy, Francesco Sala, Markus Renoldner, Mohamed Ben Abdelouahab, Davor Dobrota Past EPFL PhD Students Luca Coradello, Ondine Chanon, Riccardo Puppi Courses Numerical approximation of PDEs MATH-451 The course is about the derivation, theoretical analysis and implementation of the finite element method for the numerical approximation of partial differential equations in on
Jonathan Yuelin DongTeaching & PhD PhD Students Zhiyuan Hu Past EPFL PhD Students as codirector Yan Liu
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
Dominique BonvinDominique Bonvin is Professor and Director of the Automatic Control Laboratory of EPFL. He received his Diploma in Chemical Engineering from ETH Zürich, and his Ph.D. degree from the University of California, Santa Barbara. He worked in the field of process control for the Sandoz Corporation in Basel and with the Systems Engineering Group of ETH Zürich. He joined the EPFL in 1989, where his current research interests include modeling, control and optimization of dynamic systems. He served as Director of the Automatic Control Laboratory for the periods 1993-97, 2003-2007 and again since 2012, Head of the Mechanical Engineering Department in 1995-97 and Dean of Bachelor and Master Studies at EPFL for the period 2004-2011.
Pierre VandergheynstPierre Vandergheynst received the M.S. degree in physics and the Ph.D. degree in mathematical physics from the Université catholique de Louvain, Louvain-la-Neuve, Belgium, in 1995 and 1998, respectively. From 1998 to 2001, he was a Postdoctoral Researcher with the Signal Processing Laboratory, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. He was Assistant Professor at EPFL (2002-2007), where he is now a Full Professor of Electrical Engineering and, by courtesy, of Computer and Communication Sciences. As of 2015, Prof. Vandergheynst serves as EPFL’s Vice-Provost for Education. His research focuses on harmonic analysis, sparse approximations and mathematical data processing in general with applications covering signal, image and high dimensional data processing, computer vision, machine learning, data science and graph-based data processing. He was co-Editor-in-Chief of Signal Processing (2002-2006), Associate Editor of the IEEE Transactions on Signal Processing (2007-2011), the flagship journal of the signal processing community and currently serves as Associate Editor of Computer Vision and Image Understanding and SIAM Imaging Sciences. He has been on the Technical Committee of various conferences, serves on the steering committee of the SPARS workshop and was co-General Chairman of the EUSIPCO 2008 conference. Pierre Vandergheynst is the author or co-author of more than 70 journal papers, one monograph and several book chapters. He has received two IEEE best paper awards. Professor Vandergheynst is a laureate of the Apple 2007 ARTS award and of the 2009-2010 De Boelpaepe prize of the Royal Academy of Sciences of Belgium.
Kathryn Hess BellwaldKathryn Hess Bellwald received her PhD from MIT in 1989 and held positions at the universities of Stockholm, Nice, and Toronto before moving to the EPFL.Her research focuses on algebraic topology and its applications, primarily in the life sciences, but also in materials science. She has published extensively on topics in pure algebraic topology including homotopy theory, operad theory, and algebraic K-theory. On the applied side, she has elaborated methods based on topological data analysis for high-throughput screening of nanoporous crystalline materials, classification and synthesis of neuron morphologies, and classification of neuronal network dynamics. She has also developed and applied innovative topological approaches to network theory, leading to a powerful, parameter-free mathematical framework relating the activity of a neural network to its underlying structure, both locally and globally.In 2016 she was elected to Swiss Academy of Engineering Sciences and was named a fellow of the American Mathematical Society and a distinguished speaker of the European Mathematical Society in 2017. In 2021 she gave an invited Public Lecture at the European Congress of Mathematicians. She has won several teaching prizes at EPFL, including the Crédit Suisse teaching prize and the Polysphère d’Or.
Maryna ViazovskaMaryna Viazovska did her bachelor studies at the Kyiv National Taras ShevchenkoUniversity and completed her MSc at the Technical University Kaiserslautern.She obtained her PhD in 2013 in Bonn.She was a postdoctoral researcher at the Institut des Hautes Etudes Scientifiquesand at the Humboldt University of Berlin, and in 2017 was a Minerva DistinguishedVisitor at Princeton University. She joined EPFL in 2017 as Tenure-Track AssistantProfessor and was promoted Full Professor in 2018.
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
Xue-Mei Li-HairerTeaching & PhD PhD Students Johann Williams, Timon Miehling, Szymon Sobczak, Kexing Ying Courses Introduction to multi-scale stochastic dynamics MATH-487 This course introduces slow/fast systems and the mathematical tools used to derive effective equations governing their behaviour. Students will learn core concepts and techniques for rigorously analysing complex stochastic multi-scale systems.
