Teaching

Radboud University (2019-2023)

• Statistical machine learning (Master course) I am giving the following lectures in this course: introduction to probability theory and Bayesian inference; Gaussian processes; Markov Chain Monte Carlo; variational inference. I am also supervising some of the practical sessions.
• Machine learning in practice (Master course) I am supervising about three teams each year who participate in Kaggle competitions
• Research seminar data science (Master course): coordinator of the course in 2023. In this course we teach students to review scientific papers and cover recent advances in machine learning and data science.

Maastricht University (2014-2017)

Problem based learning

• Probability theory
• Quantitative methods
• Quantitative business and statistics