Teaching

Current teaching responsibilities

• Data Analytics (WU Vienna, Bachelor level, 60 students, SS24, WS24, SS25)

• Statistics (WU Vienna, Bachelor level, 180 students, SS24, WS24, SS25)

Student supervision

Master students

• Piotr Buczek, 2025 (ongoing)
  • WU Vienna
• Margarida Ramos Silva, 2025 (ongoing)
  • WU Vienna
• Holly Vuarnoz, 2025 (ongoing)
  • University of Zurich, co-supervised with Torsten Hothorn
• Andrea Staub, 2025
  • Selecting data modalities for clinical prediction models using deep neural networks
  • University of Zurich, co-supervised with Beate Sick
• Nicola Stella, 2024
  • Using anchor regression for out-of-distribution generalization of widely used risk prediction models
  • ETH Zurich, co-supervised with Olga Demler and Peter Bühlmann
• Andrea Götschi, 2022
  • Applications of ordinal neural network transformation models
  • University of Zurich, co-supervised with Beate Sick
• Maic Rakitta, 2021
  • Generalized linear anchor regression
  • ETH Zurich, co-supervised with Peter Bühlmann
• Tran Xuan Thanh Elsener, 2021
  • Hyperparameter tuning in linear anchor regression
  • University of Zurich, co-supervised with Beate Sick

Bachelor students

I have supervised 8 Bachelor students at WU Vienna in Data Science or Statistics.

Teaching experience

• STA406 Generalized Regression (UZH, FS19/20/21, lecturer/teaching assistant)

• STA408 Statistical methods in epidemiology (UZH, SS20, lecturer/teaching assistant)

• STA402/MAT924 Likelihood inference (UZH, FS19, teaching assistant)

• Physical chemistry for molecular medicine (ALU, SS18, teaching assistant)