**Deep Learning**2022-2023 (MSC level, VU, course coordinator) [Canvas]**Computational Intelligence**2021-2022 (BSC level, VU, course coordinator) [Canvas]**Deep Learning**2021-2022 (MSC level, VU, course coordinator) [Canvas]**Computational Intelligence**2020-2021 (BSC level, VU, course coordinator) [Canvas]**Deep Learning**2020-2021 (MSC level, VU, course coordinator) [Canvas]**Computational Intelligence**2019-2020 (BSC level, VU, course coordinator) [Canvas]**Learning Machines**2019-2020 (MSC level, VU, teacher) [Canvas]

**To all prospective students:** I am interested in the theoretical aspects of machine learning / deep learning / deep generative modeling, e.g., proposing new models and (preferably) theoretical analysis (e.g., formulating theorems, proving/showing properties). Applications of machine/deep learning are less favorable topics due to very limited computational resources at the Univeristy. From my students I expect high independence (including proposing own ideas), good understanding of mathematics (algebra, calculus, statistics, probability theory) and good programming skills (Python + ML/DL libraries, preferably PyTorch).

Please take a look at the template of a BSC/MSC thesis and get familiar with information therein.

**A thesis template**(LaTex): [Overleaf]

**BKO**: 2021, the Netherlands**Teaching qualification for higher education**: 2015, Poland