Teaching

My teaching focuses on programming, algorithms, and scientific computing, ranging from introductory programming in the first year of the Bachelor's program to advanced software concepts for scientific computing at Master's level.

A recurring theme is the connection between mathematical and algorithmic ideas and their practical implementation. Students should not only learn how to write programs, but also how to structure computational problems, reason about algorithms, test implementations, and develop reliable scientific software.

Current and recurring courses

Programmieren – Grundlegende Konzepte

Bachelor Mathematics · 1st semester · Math-Ba-PR10

An introduction to programming for mathematics students. The course develops fundamental programming concepts such as control flow, functions, data types, recursion, and basic algorithms, while connecting them from the beginning to mathematical problems and computational thinking.

The course is designed for students with very different levels of previous programming experience and provides the foundation for the subsequent course Programmieren – Weiterführende Konzepte.

Current course: WS 2026/27
Previous course: WS 2025/26

Programmieren – Weiterführende Konzepte

Bachelor Mathematics · 2nd semester · Math-Ba-PR20

This course builds on the programming foundations from PR10 and introduces central concepts of modern algorithmics. Topics include classical algorithms and data structures, algorithm design strategies, runtime analysis, graph algorithms and algorithmic geometry.

At the same time, programs are increasingly treated as structured systems: students learn to define their own data types, organize code modularly, and systematically test implementations. The course connects algorithmic thinking, mathematical modelling, and modern programming practice.

Current course: SS 2026

Scientific Programming – Advanced Concepts

Master Mathematics / Computational Modeling and Simulation · Math-Ma-33

This course addresses concepts and techniques for developing modern scientific software in C++. Starting from generic programming and the C++ type system, we investigate abstractions used in numerical software, including templates, concepts, iterators, function objects, data structures, and techniques for writing efficient and reusable code.

A central objective is to connect software design with the requirements of numerical algorithms: students learn to reason about interfaces, correctness, performance, testing, and maintainability rather than treating implementation as a final step after the mathematics.

Current course: WS 2026/27

Student projects and theses

I regularly supervise Bachelor's and Master's theses as well as research and programming projects in numerical mathematics and scientific computing. Many topics arise directly from current research and range from numerical experiments and software development to mathematical analysis.

Current project and thesis topics

Previous courses