Staff

Prof. Jacek Tabor
  • clustering methods
  • information theory
  • entropy based classification
Prof. Igor T. Podolak
  • hierarchical classification
  • deep learning
  • learning theory
Prof. Adam Roman
  • software testing and quality
  • automata and formal languages
  • classification theory
Prof. Tomasz Trzciński
  • computer vision
  • machine learning
  • representation learning
Dr Jarek Duda
  • information theory
  • machine learning
  • bioinformatics
  • algorithm complexity
  • graph theory
  • physics
Dr Stanisław Jastrzębski
  • drug discovery
  • optimization
  • deep learning
Dr Krzysztof Misztal
  • image processing
  • biometrics methods
Dr Przemysław Spurek
  • compression theory
  • clustering methods
Dr Łukasz Struski
  • machine learning
  • deep learning
Dr Marek Śmieja
  • clustering methods
  • entropy theory
  • semi-supervised learning
Dr Bartosz Zieliński
  • gramatics inference
  • image processing
  • computer vision

PhD students

Klaudia Bałazy
  • deep learning
  • natural language processing
  • representation learning
Andrzej Bedychaj
  • independent component analysis
  • compression algorithms
Adriana Borowa
  • computer vision
  • biomedical imaging
  • interpretability
Jakub Chłędowski
  • computer vision
  • ml in cancer detection
  • natural language processing
Tomasz Danel
  • generative models
  • convolutional neural networks
  • bioinformatics
Krzysztof Galias
  • reinforcement learning
  • deep learning
  • AI safety
Szymon Knop
  • generative models
  • autoencoders
  • computer vision
Damian Leśniak
  • cheminformatics
Łukasz Maziarka
  • cheminformatics
  • graph convolutional neural networks
  • natural language processing
Aleksandra Nowak
  • disentanglement learning
  • neural architecture search
Michał Pietruszka
  • natural language processing
  • sequence-to-sequence models
Agnieszka Pocha
  • deep learning
  • cheminformatics
Dawid Rymarczyk
  • computer vision
  • medical imaging
  • active learning
  • interpretability of neural networks
Michał Sadowski
  • computer vision
  • generative models
  • visual reasoning
Marcin Sendera
  • generative models
  • multi-task & meta-learning
  • natural language processing
Igor Sieradzki
  • generative models
  • reinforcement learning
Damian Stachura
  • adversarial examples
  • reinforcement learning
  • continual learning
Maciej Szymczak
  • natural language processing
  • theory of programming languages
Konrad Walkowicz
  • deep learning
  • high performance machine learning
Magdalena Wiercioch
  • learning
  • data clustering
  • natural language processing
Maciej Wołczyk
  • reinforcement learning
  • generative models
  • continual learning
Bartosz Wójcik
  • deep learning
  • clustering methods
  • generative models
Michał Zając
  • reinforcement learning
  • adversarial examples
Konrad Żołna
  • deep learning
  • imitation learning

Former members

Dr Wojciech M. Czarnecki

Contact Us

Group of Machine Learning Research
Faculty of Mathematics and Computer Science
ul. Lojasiewicza 6
30-342, Cracow, Poland