Michał Jan Włodarczyk Email: mwlodarzc@gmail.com [GitHub] [Google Scholar] [Linkedin] The Faculty of Mathematics and Information Science Warsaw University of Techonlogy, Warsaw, Poland Bio | Academic Achievements | Research Experiences | Connections

Bio

I obtained a B.Eng. in Automation and Robotics from Wrocław University of Science and Technology (WUST) in 2024. Currently, I am pursuing a Master’s degree in Computer Science with a specialization in Artificial Intelligence at the Warsaw University of Techonlogy (WUT), under the supervision of Prof. Przemysław Musialski.

I am deeply passionate about science and engineering and aspire to contribute to high-impact fields within Machine Learning. My research interests focus on developing interpretable models with large learning capacities. At present, I am particularly interested in the science of cognition, as well as Variational Autoencoders (VAEs), Implicit Neural Representations (INRs) and Diffusion models.

Beyond my current work in machine learning, I also have a strong interest in Robotics and Reinforcement Learning.

Academic Achievements

^{†Equal Contribution, * Corresponding Author(s)}

Conference Papers

[1] Gruszczynski, G., Meixner, J.J., Włodarczyk, M.J., and Musialski, P., "Beyond Blur: A Fluid Perspective on Generative Diffusion Models", International Conference on Computer Vision (ICCV), 2025.

[2] Yin, H., Plocharski, A., Włodarczyk, M.J., Kida, M., and Musialski, P., "FlatCAD: Fast Curvature Regularization of Neural SDFs for CAD Models", Pacific Graphics, 2025.

Conference Presentation

[3] Włodarczyk, M.J. and Musialski, P., "Photorealistic Reconstruction with Differentiable Rendering", Presentation at the Data Science Summit — Machine Learning Edition, June 13, 2024.

Research Experiences

• IDEAS NCBR, Warsaw, Poland
  Research Intern in Computer Graphics Group
  October 2023 – February 2025
  
  
  
  • Developed, trained, and fine-tuned machine learning models
  • Designed and executed large-scale experiments and benchmarks
  • Orchestrated distributed high-performance computing workflows
  • Analyzed results and presented insights to guide research directions
  • Co-authored contributions to peer-reviewed research publications
  • Presented technical findings to academic and non-specialist audiences
• Mi2Lab, Warsaw, Poland
  Contract Developer
  April 2025 – June 2025
  
  
  
  • Conducted literature review to identify key research directions
  • Mapped research findings to highlight directions worth exploring
  • Designed and implemented a reproducible data analysis framework
  • Developed and refined neural network–based reconstruction methods
  • Evaluated performance across architectures and parameter spaces
  • Leveraged HPC resources for large-scale training and optimization
  • Compiled final report integrating research and experimental findings

Connections

Przemyslaw Musialski Grzegorz Gruszczyński Aleksander Płocharski Jan Świdziński Haotian Yin

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