About me

I’m a PhD student at the Jagiellonian University, working on machine learning with the GMUM group under supervision of Prof. Jacek Tabor. My main research interests are centered around the issue of efficiency in deep learning, highlighting the following questions in particular:

  • Continual Learning – how to remember the past and reuse it efficiently when learning from a stream of data.
  • Conditional Computation – how to adapt the computing power of the model to a given example.
  • Generative Models – how to perform weakly supervised conditional generation and adapt existing models for conditional generation.
  • Reinforcement Learning – how to increase the sample efficiency and leverage privilged data during training.
  • Imitation Learning – how to combat distribution shift when learning from expert data.


  • (March 2022) Started a research internship with João Sacramento at ETH Zurich!
  • (December 2021) PluGeN, our paper on introducing supervision to pre-trained, was accepted to AAAI 2022.
  • (September 2021) Two of our papers, Zero Time Waste and Continual World were accepted to the NeurIPS 2021 conference as poster presentations.
  • (September 2021) A paper on closed-loop imitation learning for self-driving cars, which I worked on during my internship at Woven Planet, was accepted to CORL 2021 conference.
  • (July 2021) I was named a “best reviewer” (top 10% best scored reviewers) at ICML 2021.
  • (April 2021) Our proposal for funding a ML & neuro summer school was accepted in the Nawa Spinaker program! The school is planned for June 2022 in Kraków.
  • (April 2021) Started my internship at Woven Planet Level-5 (previously Lyft Level-5), working on imitation learning for planning in self-driving cars.
  • (February 2021) Presented my student abstract on investigating the role of batch size in experience replay methods for continual learning at AAAI 2021.
  • (August 2020) Our paper on conditional semi-supervised generation with mixtures of Gaussians was published in IEEE Transactions on Neural Networks and Learning Systems.
  • (July 2020) Co-organized the EEML 2020 summer school.
  • (December 2019) Presented a paper on biologically-inspired spatial neural networks at the NeurIPS 2019 workshop “Real Neurons & Hidden Units”.
  • (November 2019) Co-organized a tutorial on reinforcement learning at the MLinPL conference.
  • (October 2019) Started my PhD at the Jagiellonian University with GMUM.

Selected publications

Scheme of PluGeN
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models
Maciej Wołczyk*, Magdalena Proszewska*, Łukasz Maziarka, Maciej Zięba, Patryk Wielopolski, Rafał Kurczab, Marek Śmieja
AAAI 2022
Scheme of the Zero Time Waste model
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks
Maciej Wołczyk*, Bartosz Wójcik*, Klaudia Bałazy, Igor Podolak, Jacek Tabor, Marek Śmieja, Tomasz Trzciński
NeurIPS 2021
[Paper] [Code]
CW20 from Continual World
Continual World: A Robotic Benchmark For Continual Reinforcement Learning
Maciej Wołczyk*, Michał Zając*, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś
NeurIPS 2021
[Webpage] [Paper] [Code]