IE Toppforsk: Partial Differential Equations
Partial differential equations
Toppforsk@IE research group
Introductory lectures on Wasserstein gradient flows
Introductory lectures on Wasserstein gradient flows
Date: December 14-15, 2026
Place: Auditorium EL1
Filippo Santambrogio, Institut Camille Jordan, Université Lyon 1, France
The motivation for this course dates back to the work of Jordan, Kinderlehrer and Otto who found a variational structure for the Fokker-Planck equation, i.e. the heat equation with a gradient drift in conservative form. They proved that this equation is the gradient flow of a relative entropy in the Wasserstein metric, induced by optimal transport, and analyzed a time-discrete scheme, now called JKO scheme, which approximates the solutions. This paved the way to the study of many other equations sharing the same structure. In the course we will provide the necessary background in terms of optimal transport and of the general theory of gradient flows, analyze the convergence of the JKO scheme, and study the properties of this discrete approximation.
Monday 10:15-12:00: Introduction to optimal transport, Wasserstein distances, and curves of measures.
Monday 13:15-15:00: Introduction to gradient flows in Euclidean and metric spaces, and to the case of the Wasserstein space, with a formal derivation of the corresponding PDE.
Tuesday 10:15-12:00: Rigorous proof of convergence for the easiest case (Fokker-Planck) and how to adapt to nonlinear equations.
Tuesday 13:15-15:00: Complementary material. Other PDEs with a gradient flow structure, applications and estimates.
Introductory lectures on kinetic theory for conservation laws
Introductory lectures on kinetic theory for conservation laws
Date: May 19-20, 2026
Place: Auditorium F4
Nathaël Alibaud, Université Marie et Louis Pasteur, LmB, UMR CNRS 6623, France; and SUPMICROTECH, Franc
This course is devoted to the kinetic formulation of scalar conservation laws (SCLs), inspired by the analysis of kinetic models from statistical physics, such as the Boltzmann and Vlasov equations, and adapted to SCLs by Pierre-Louis Lions, Benoît Perthame, and Eitan Tadmor in 1991. The kinetic approach provides a robust framework for the analysis of SCLs, yielding well-posedness results in the purely integrable setting and allowing one to establish stability properties through weak compactness arguments alone. As a guiding example, particular attention will be devoted to the method of compensated compactness, originally introduced by Luc Tartar in 1979 to capture regularizing effects arising solely from the genuine nonlinearity of the flux. We will explain how to recover such results within the kinetic framework through Fourier-analytic techniques and averaging lemmas
Tuesday 10:15-12:00: Formulation via vanishing viscosity
Tuesday 13:15-15:00: Well-posedness
Wednesday 10:15-12:00: Well-posedness/Compensated compactness I
Wednesday 13:15-15:00: Compensated compactness II
An introductory lecture series on Stochastic PDEs and Interval Arithmetic in Computer-Assisted Proofs
An introductory lecture series on Stochastic PDEs and Interval Arithmetic in Computer-Assisted Proofs
Date: December 8-11, 2025
Place: Auditorium H1 (Monday-Wednesday), Auditorium EL2 (Thursday)
Julien Vovelle, UMPA, ENS de Lyon
We give an introduction to stochastic partial differential equations, discussing in particular regularization by noise, invariant measures, and the stochastic compactness method for first and second order conservation laws.
Monday 10:15: Quick introduction to the Wiener process and the stochastic integral
Monday 14:15: Itô formula, regularization by the noise in transport equations
Tuesday 10:15: The stochastic compactness method I
Tuesday 14:15: The stochastic compactness method II. Invariant measures
Javier Gomez-Serrano, Brown University
In this series of lectures I will discuss how computers can be used for discovery, intuition, computation and mathematical proofs, using a broad collection of problems.
Wednesday 10:15: Introduction
Wednesday 14:15: Computer-assisted proofs (I)
Thursday 10:15: Computer-assisted proofs (II)
Thursday 14:15: AI+Math
Project advisor

Photo © Kai T. Dragland (2025)