Teaching

Applied quantitative training

My teaching is about making quantitative methods feel usable. I help students move from statistical reasoning to applied econometric analysis in R, with attention to what the numbers mean in real empirical work. Across lectures and tutorials, I have tried to keep technical tools clear, practical, and close to the questions students actually need to answer.

Teaching experience

Lecturer Autumn Semesters 2023–24, 2024–25, 2025–26

Econometrics (Économétrie TP)

Faculty of Economics and Business (SECO), University of Neuchâtel

Course details

Applied tutorial course focused on regression analysis, model diagnostics, and the practical use of R for empirical work.

Topics and skills

  • Introduction to regression analysis and the classical linear regression model
  • Residual analysis, diagnostics, and influence measures
  • Generalized regression models, heteroskedasticity, and autocorrelation
  • Comparison of estimators using applied datasets
  • Critical discussion of empirical studies using basic econometric methods
Teaching Assistant Autumn Semester 2020–21

Quantitative Methods II

Department of Law and Political, Economic, and Social Sciences (DIGSPES), University of Eastern Piedmont (UPO), Alessandria

Tutor September 2020–April 2022

Statistics and Quantitative Methods

Department of Law and Political, Economic, and Social Sciences (DIGSPES), University of Eastern Piedmont (UPO), Alessandria

Tutoring activities covered Statistics, Economic Statistics, Mathematical Methods, and Quantitative Methods.