Courses at Vrije Universiteit Amsterdam



  • 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]

Supervision of BSC/MSC Students



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.

 

Teaching Qualifications

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