Prof. Dr. Richard Höfer

We develop the theory of Optimal Transport, which play a fundamental role in many areas of mathematics including geometry, analysis and stochastics and has various applications in computer science and economy. 
The theory goes back to the Monge formulation in the 18th century. The seminal reformulation due to Kantorovitch from the 1940s, which has been rewarded with the Nobel prize for economy, has laid thethe foundation for the modern theory of Optimal Transport. 

This course gives an introduction to the theory of Optimal Transport. In particular, we analyze the Monge and the Kantorovitch formulation, we introduce Wasserstein distances as a metric on the space of probability measures that metrizes weak convergence, and we consider applications to mean field limits of interacting particle systems.

Stochastic processes are the fundamental objects for time dependent phenomena that involve randomness. Applications range from physics, biology, and chemistry over information theory, machine learning, to finance.

We study stochastic processes both in discrete and continuous time. The content of the course includes conditional expectations, Markov chains and processes, martingals, recurrence and transience, Poisson processes, random walks, Brownian motion.


There will be a course Stochastic Analysis in summmer 2026 where we develop the theory of stochastic integration and stochastic differential equations.

Seminar zu ausgewählten Themen der Wahrscheinlichkeitstheorie. Z.B: Irrfahrten, Ploya-Urnen, große Abweichungen, charakteristische Funktionen, 0-1 Gesetze.

Stochastic processes are the fundamental objects for time dependent phenomena that involve randomness. Applications range from physics, biology, and chemistry over information theory, machine learning, to finance.

We study stochastic processes both in discrete and continuous time. The content of the course includes conditional expectations, Markov chains and processes, martingals, recurrence and transience, Poisson processes, random walks, Brownian motion.


There will be a course Stochastic Analysis in summmer 2026 where we develop the theory of stochastic integration and stochastic differential equations.

Homogenization is concerned with the rigorous derivation of effective macroscopic models for materials with microscturctures, for example porous media or elastic composite material. A prototype problem is the limiting behavior of an elliptic PDE with rapidly oscillating coefficients.
In this seminar, we will study methods such as two-scale convergence and Gamma-convergence and apply them to different homogenization problems.

Irrfahrten sind diskrete stochastische Prozesse, die zufällige
Bewegungen auf dem Gitter $\Z^d$ modellieren. Sie sind ein wichtiges
Thema der Wahrscheinlichkeitstheorie mit Anwendungen in der
Finanzmathematik und Physik.
In diesem Seminar werden wir mit elementaren stochastischen Methoden
Eigenschaften von Irrfahrten untersuchen.
Gegebenenfalls werden wir uns zudem mit theoretischem Hintergund und
Verallgemeinerungen wie Markovketten und Martingalen befassen.

The lecture series gives an introduction to the theory of partial
differential equations (PDEs). In the first part we will study classical
solution theories for PDEs. In particular we will discuss some
fundamental equations and examples and show limitations of classical
solution concepts. In the second part of the lecture series an
introduction to the modern theory of PDEs is given, which is based on a
weaker notion of solutions and functional analytic concepts. In
particular we will study elliptic PDEs.

We continue the study of elliptic partial differential equations from
the lecture series "Partial Differential Equation I". The content is
disjoint from the content of the lecture series "Partial Differential
Equation I" of previous years. The following content is planned:


- Schauder and L^p estimates for linear equations by the Campanato approach

- Harnack inequality and DeGiorgi-Nash-Moser Theorem

- Meyers' estimate

- Existence and regularity for some nonlinear elliptic equations e.g. by compactness and variational methods

The lecture series gives an introduction to the theory of partial differential equations (PDEs). In the first part we will study classical solution theories for PDEs. In particular we will discuss some fundamental equations and examples and show limitations of classical solution concepts. In the second part of the lecture series an introduction to the modern theory of PDEs is given, which is based on a weaker notion of solutions and functional analytic concepts. In particular we will study elliptic PDEs.