PhD student in Computer Science · Machine Learning Researcher · Jagiellonian University
I'm a PhD student in Computer Science at Jagiellonian University, working on machine learning, computer vision, and generative models — mainly applied to medical imaging.
Research
Primary PhD focus: applying machine learning and computer vision to multimodal medical data for diagnostic and research purposes.
Includes Gaussian Splatting for representing medical volumetric data, interpolation, and 3D mesh reconstruction.
Publications
Ignacy Kolton, Kacper Marzol, Paweł Batorski, Marcin Mazur, Paul Swoboda, Przemysław Spurek
arXiv preprint arXiv:2602.00350 · 2026
Machine unlearning is a key defense mechanism for removing unauthorized concepts from text-to-image diffusion models, yet recent evidence shows that latent visual information often persists after unle...
Kacper Marzol, Ignacy Kolton, Weronika Smolak-Dyżewska, Joanna Kaleta, Marcin Mazur, Przemysław Spurek
arXiv preprint arXiv:2509.16806 · 2025
Multi-modal three-dimensional (3D) medical imaging data, derived from ultrasound, magnetic resonance imaging (MRI), and potentially computed tomography (CT), provide a widely adopted approach for non-...
Background
Education
2026 - present
Jagiellonian University · Krakow, Poland
2024 - 2026
Jagiellonian University · Krakow, Poland
2021 - 2024
Jagiellonian University · Krakow, Poland
Experience
05.2024 - 11.2024
HERE Technologies
Grant
ArtInCom Minigrant (2025) — Research minigrant from the Artificial Intelligence Computing Core Facility (ArtInCom) supporting student-led research.
Machine Learning & AI
Machine Learning, LLMs, NLP, PyTorch, NumPy, pandas
Programming Languages
C++, Python, .NET, C#, Java, Shell, Assembler
Software Engineering
OOP, SOLID, Design Patterns, Unit Testing, PyTest, Google Test
DevOps & Tools
Git, GitLab, CI/CD, Docker, Jira, Agile
Systems
Linux, macOS, Windows
Databases
SQL
Mathematics
Statistics, Calculus, Linear Algebra
Contact
Open to research collaboration, PhD-adjacent projects, or just a good conversation about ML and medical imaging. Reach out if you want to collaborate!