Past lectures

Statistics for Data Science
Free University of Berlin (Wintersemester 2024/25)

• Course page

Quasi-Monte Carlo methods for PDE uncertainty quantification
Centrum Wiskunde & Informatica (CWI) (fall 2024)

• Autumn school course page

Inverse problems
Free University of Berlin

• Course page (Sommersemester 2023)
• Course page (Sommersemester 2022)

Uncertainty quantification and quasi-Monte Carlo
Free University of Berlin (Wintersemester 2022/23)

• Course page

Special course on inverse problems
LUT University (spring 2021)

Lecture notes on the construction of the tomography matrix and a computational inversion example using total variation regularization with the iterative Chambolle–Pock algorithm (spring 2021).

• Introduction to X-ray tomography (tomodemo.m)
• Total variation regularization for X-ray tomography (tvdemo.m, sinogram.mat)

Numerical methods for uncertainty quantification
LUT University (fall 2020)

The introductory lecture notes I wrote about the stochastic Galerkin method as part of the Seminar on Computational Engineering at LUT University (fall 2020).

• Numerical methods for uncertainty quantification

Sparse grid methods
University of Mannheim (fall 2019)

The introductory lecture notes I wrote for the Sparse grid methods block seminar at University of Mannheim (fall 2019).

• Sparse grid methods (part 1)
• Sparse grid methods (part 2) (SmolyakQuadrature.zip)

Applications of matrix computations
University of Helsinki (spring 2018)

The lecture notes I wrote for the Applications of matrix computations course at University of Helsinki (spring 2018).

• The power method
• Stochastic matrices, PageRank, and the Google matrix
• Numerical integration
• Finite difference methods (isospectral.m)