Mathematics for Artificial Intelligence 1–3
I designed and built this three-semester lecture series for JKU's “Artificial Intelligence” degree: mathematics at the level of “Math for Physicists,” tuned to AI, and built for distance learning from the ground up. It was recognised with the Kepler Award for Excellence in Digital Teaching and nominated for the national Ars Docendi prize.
I also developed the Master's elective track “Mathematical Foundation of AI,” and I am responsible for up to 20 AI students in the seminar “Mathematical foundations of AI,” which is designed to attract them to mathematics.
Mathematics for Quantum Science 1–3
I am currently building this new three-semester series for the Quantum Science & Technology programme (starting WS 2026), adapting the approach proven in Mathematics for AI to the language and needs of quantum science.
Selected courses
- Operator theory for Machine Learning
- Classical harmonic analysis
- Approximation theory for Machine Learning
- Mathematics for Artificial Intelligence 1–3
- Information-based complexity
- High-dimensional numerical integration
- Modern methods in Approximation theory
- Analysis 1 & 2
- Complex analysis