“If you want to master something, teach it. The more you teach, the better you learn.” – Richard Feynman

Teaching Experience as PhD Candidate:

  • Winter Term, 2024/2025
    • Statistics for Geosciences (Lecture and Exercise)
    • Debating statistical inference schools: Frequentism, Bayesianism, Fiducialism, and beyond (Seminar)
  • Summer Term, 2024
    • Causality (Exercise)
  • Winter Term, 2023/2024
    • Statistics for Geosciences (Lecture and Exercise)
    • Selected Topics in Decision Theory (Seminar)
    • Statistical Inference (3 lectures as substitute, ~170 students)
  • Summer Term, 2023
    • Causality (Exercise)
  • Winter Term, 2022/2023
    • Statistics for Geosciences (Lecture and Exercise)
    • Economic and Social Statistics (Lecture and Exercise)
  • Summer Termin, 2022
    • Basic Probability Theory (Exercise)
    • Statistics as Minor IV (Lecture and Exercie)
  • Winter Term, 2021/2022
    • Statistics for Geosciences (Exercise)
    • Economic and Social Statistics (Lecture and Exercise)
    • Probability Theory and Inference I (Exercise)

Besides, I (co-)supervise BSc and MSc theses in statistics (5 completed).

I also taught some undergraduate courses during my master’s:

  • Summer Term, 2021
    • Introduction to Probability Calculus and Inferential Statistics (Tutorial)
  • Winter Term, 2019/20
    • Generalized Regression Models (Tutorial)
  • Summer Term, 2019
    • Linear Models (Tutorial)

Potential Topics for Bachelor/Master Theses under my co-supervision:

  • De-biased Boosting from Complex Samples
  • Survey on Continual Learning (Literature research)
  • Bayesian Optimization - a Decision-Theoretic Perspective
  • Lipschitz-Regularization in Deep Learning
  • Horvitz-Thompson Estimation from Bayes-optimal Data

If you are interested in one of those topics, please reach out and I will provide you with literature.