Jakub Tomczak

I am an assistant professor of Artificial Intelligence in the Computational Intelligence group (led by Prof. A.E. Eiben) at Vrije Universiteit Amsterdam. My main research interests include deep learning, Bayesian inference and deep generative modeling.

Collaborators (current)



  • Ewelina Węglarz-Tomczak (UvA): systems biology [info]
  • Emiel Hoogeboom (UvA): deep generative modeling [info]
  • Guszti Eiben (VU): computational intelligence [info]
  • Mark Hoogendoorn (VU): machine learning [info]
  • Annette ten Teije (VU): knowledge representation [info]
  • Max Welling (UvA): deep learning & machine learning [info]
  • Tameem Adel (Univ. of Liverpool): deep generative modeling with MIL [info]
  • Erik J. Bekkers (UvA): deep learning: equivariance, explainability [info]
  • Alessandro Zonta (VU): learning urban behaviors using EAs and VAEs [info]

PhD students



  1. Anna Kuzina (VU): deep generative modeling and continual learning
  2. David Romero (VU): equivariant neural networks and attention
  3. Emile van Krieken (VU): learning discrete structure
  4. Jie Luo (VU): learning in evolutionary robotics
  5. Maximilian Ilse (UvA): deep learning and causality for medical data
  6. Sharvaree Vadgama (UvA): deep learning and explainability
  7. Annet Onnes (UvA): monitoring of adaptive systems
 

MSc students

  1. Xingkai Wang (VU): Variational Auto-Encoders with reversible computing
  2. Mick Ijzer (VU): Variational Auto-Encoders with non-trainable components
  3. Nihat Uzunalioglu (VU): Generative Attention-based Multiple Instance Learning
  4. Michael Accetto (VU): "Exploration of the internal representation of flow based generative models"

Former students



PhD students

  1. Szymon Zaręba [info]
  2. Gongjin Lan (VU): learning controllers of evolvable robots
 

MSc students:

  1. Justus Huebotter (VU): spiking neural networks and auto-encoders
  2. Falko Lavitt (VU): Automatic cell counting using deep learning
  3. Ioannis Gatopoulos (UvA-VU): "Self-Supervised Variational Auto-Encoders"
  4. Ilze Auzina (VU): "ABC-Di: Approximate Bayesian Computation for discrete data"
  5. Burcu Kucukoglu (VU-CWI): "Biologically Plausible End-to-end Deep Reinforcement Learning"
  6. Lena Shutko (VU)
  7. Esther Kuikman (VU)
  8. Mats Valk (VU)
  9. Dorien Verbruggen (VU)
  10. Felix Vink (VU)
  11. Yi-Ting Lin (VU)
  12. Meagan Tjon Sjoe Sjoe (VU)
  13. Yannick Hogebrug (VU)
  14. Jerry Timmer (VU)
  15. Tim Davidson (UvA) [info]
  16. Jasper Linmans (UvA) [info]
  17. Philip Botros (UvA) [info]
  18. Marco Federici (UvA) [info]
  19. Szymon Zaręba (PWr) [info]
  20. Przemysław Kłysz (PWr) [info]
  21. Marcin Kocot (PWr)