Teaching
Teaching Assistant Positions
2026
Physics 1 for Physicists
ETH Zurich
2026
Physics 2 for Electrical Engineering
ETH Zurich
2025
Physics 2 for Material Science
ETH Zurich
2024
Quantum Information Processing 2
ETH Zurich
2020 – 2022
Statistical Methods of Data Analysis
University of Vienna
I designed and taught the exercise classes on descriptive and inferential (likelihoods, Bayes, …)
statistics for physics graduate students.
2018 – 2019
Electrodynamics I
TU Vienna
I supervised one of the exercise classes on electrodynamics and special relativity for physics
undergraduate students.
Lectures and Seminars
- CERN Quantum Technologies Lecture Series, 2023: Superconducting thermometers for the direct detection of dark matter.
- Inverted CERN School of Computing, 2023: Introduction to Reinforcement Learning.
- Summer school on artificial intelligence of the Austrian Academy of Sciences, 2021: Introduction to deep learning in PyTorch.
Students I worked with
- Iancu Scurtu (ETH, semester thesis, 2026)
- Jakov Wallbrecher (ETH, semester thesis, 2026)
- Elizabeth Kunz (ETH, internship, 2026)
- Geneviève Gervais (ETH, internship, 2026)
- Emre Vardar (ETH, master thesis, 2026)
- Michael Kerschbaum (ETH, PhD thesis, 2025)
- Peter Mukovskiy (ETH, semester thesis, 2025)
- Mattéo Maury (ETH, semester thesis, 2025)
- Susan Filisetti (ETH, internship, 2025)
- Tilly Schaaf (ETH, semester thesis, 2025)
- Romeck Kloezen (ETH, semester thesis, 2024)
- David Tartarotti (HEPHY, bachelor thesis, 2023)
- Kolos Niedermayer (HEPHY, bachelor thesis, 2023)
- Damir Rizvanovic (HEPHY, master and project thesis, 2022)
- Moriz Lackner (HEPHY, master thesis, 2022)
- Fatih Okcu (HEPHY, project thesis, 2023)
- Matthias Eiselt (HEPHY, project thesis, 2021)
- Matthias Kettner (HEPHY, project thesis, 2021)
- Pascal Schanner (HEPHY, bachelor thesis, 2021)