Teaching
I teach courses on applied econometrics and machine learning methods for economics and business students.
Recent Lectures
Applied Data Science: Machine Learning
A doctoral-level course introducing machine learning methods with applications to business and economics. Topics include regularization methods, tree-based models, neural networks, and causal machine learning.
Course materials will be available here.
Advanced Econometrics
Designed as a core PhD econometrics sequence, this course builds the estimation toolkit first, then moves to advanced applications. The lecture blocks span multiple sessions and combine theory with applied examples, with emphasis on identification, inference, and transparent implementation.
It covers panel data and GMM, causal identification with IV and modern diff-in-diff, time-series fundamentals, and an introduction to statistical learning ideas via specification choice and penalized regression.
Teaching Experience
Interim Professor (Vertretungsprofessur W2)
Teaching doctoral courses in Advanced Econometrics and Applied Data Science: Machine Learning at the Center for Doctoral Studies in Business (CDSB).
Economic and Social Statistics (Lecture)
Tutorials
During my time at Heidelberg University, I taught tutorials for Bachelor- and Master-level courses:
Family Economics
Empirical Economic Research
I developed the full set of tutorial materials, including problem sets, lab session materials, mock exams, and a standardized exam template.