Teaching
Current courses
- Mathematical Statistics (Winter)
- Fortgeschrittene Mathematische Methoden in der Statistik (Winter)
- Seminar: Theoretical Foundations of Deep Learning (Winter)
- Statistical Learning Theory (Summer) [notes 2024]
- Methoden der Linearen Algebra in der Statistik (Summer) [notes 2024]
Lecture notes
Awards
Teacher of the Year 2020, Faculty of Science, Leiden University
Thesis supervision
My group is supervising theses at both BSc and MSc levels, on a wide range of topics. Our group’s primary interest is in developing and understanding statistical methods and models. Here’s a non-exhaustive list of areas of particular interest:
- Copulas and other dependence models
- Functional data analysis
- Time series
- Probabilistic machine learning
- Statistical learning theory
- Bootstrap, cross-validation, and other resampling methods
- Multi-objective optimization
Of course, theses about these topics may involve applications to real problems in environmental sciences, engineering, finance, insurance, etc.
Interested LMU students may send an email with a recent transcript and indication of their interests.
Past highlights
A. Razawy:
Spline Based Estimation for Sufficient Dimension Reduction
D. Krüger:
General vine copula models for stationary multivariate time series
R. Weber:
Value at Risk Estimation with Subset Simulation
A. Kreuzer:
Analysing the spatial dependency among fire danger indices
A. Brauer:
Kernel estimation of conditional copula densities