Teaching

• Analysis of Variance and Experimental Design, Autumn Semesters 2023, 2024.

• Student Seminar in Statistics: E-Values and Anytime-Valid Inference, Spring Semester 2024.

• Introduction to Machine Learning, Spring Semester 2023.

Supervision of Master Theses

• Distributional Conformal Prediction, H. Höhenberger (Spring Semester 2024).
• Expectation-Calibrated Prediction Sets, D. Schaub (ongoing).