Teaching

ETH Zurich

• Wahrscheinlichkeitstheorie und Statistik: (D-ITET), HS23, TA and coordination
• Stochastik: (D-MAVT, D-MATL), HS21, TA and coordination
• Machine Learning in Finance: ETHZ, FS20, FS21, project supervision
• Mathematical Foundations of Finance: ETHZ, (D-MATH), HS19, TA
• Wahrscheinlichkeit und Statistik: ETHZ, (D-INFK), FS19, TA and coordination
• Stochastik: ETHZ, (D-MAVT, D-MATL, RW), HS18, TA

Vienna University of Business and Economics

• Optimization: WU Vienna, (QFin), FS18, TA
• Statistics I: WU Vienna, (QFin), HS17, TA

Technical University of Vienna

• Risk Management in Finance and Insurance: TU Vienna, FS16, TA

Co-Advised Theses

Master Theses

• Feature Learning in Infinite-Width Neural Networks: by Sebastian Schein (ETH), 2022
• On the Inductive Bias Towards Multi-Task Learning of $L^2$-Regularized ReLU Networks: by Sven Rosenthal (ETH/UZH), 2022
• Bayesian Optimization with Neural Networks: by Marius Högger (UZH), 2020

Semester Theses

• ML-based Uncertainty Quantification on Real World Data: by Aurelio Dolfini (ETH), 2022