October 2026–present
Research staff member
Jagiellonian Center for Artificial Intelligence
Research in artificial intelligence at Jagiellonian University.
Profile
About
Research, engineering, and the questions that connect them.
Perspective
Thoughtful research, useful systems.
I develop and study AI methods that learn from visual and structured information, make decisions, and interact with the world. My work ranges from efficient visual perception and active exploration to broader machine learning and software engineering. I enjoy moving between a precise research question and the practical decisions needed to make a system dependable.
Collaboration is central to how I work. I care about clear evidence, reusable tools, and explanations that make technical ideas accessible beyond their immediate field.
Selected experience
Experience
2022–September 2026
Doctoral researcher
IDEAS NCBR
Research on efficient visual exploration, active perception and embodied AI. Led an NCN Preludium project and mentored master’s students.
June–September 2026
Visiting PhD student
Max Planck Institute for Informatics
Research visit with the Computer Vision Group on self-supervised concept discovery.
2024–2026
Researcher
Jagiellonian University · GMUM Group of Machine Learning Research
Studied computer vision methods for pathogen detection and classification in the sepsis research project.
July 2021–December 2022
Machine Learning Engineer
AGH University of Krakow
Developed machine learning methods for CT-based lung cancer diagnosis in the X-rAI project.
July–September 2020 · Zürich, remote
Software Engineering Intern
Google · YouTube
Improved YouTube Content ID matching through large-scale analysis of repetitive video fragments, reducing false-positive early matches by 82%.
July–September 2019 · Zürich
Software Engineering Intern
Google · Android Frameworks
Built high-performance on-device logging using compile-time Java code generation, and improved tools for debugging Android window transitions, including the Winscope ADB proxy.
July–September 2017 · London
Software Engineering STEP Intern
Google · Android Enterprise
Implemented a security feature for G Suite Mobile Management as part of the Android for Corp team.
Academic background
Education
October 2022–present
PhD candidate in Computer Science
Jagiellonian University
Thesis submitted in 2026: Learning to look and search: Efficient visual exploration for embodied agents. Supervisor: Prof. Bartosz Zieliński.
October 2020–July 2022
MSc in Computer Science, with honours
Jagiellonian University
Machine learning specialisation; master’s research on interpretable multiple-instance learning.
October 2016–July 2019
BSc in Computer Science
Jagiellonian University
Theoretical computer science specialisation.
Grants & recognition
Recognition
NCN Preludium
Principal investigator of a project on uncertainty-guided active visual exploration.
FNP START
Scholarship of the Foundation for Polish Science.
Academic community
Service
Research mentoring
Mentored two MSc students who were subsequently admitted to PhD programmes.
Peer review
Reviewed for NeurIPS, IJCV, WACV, KDD and a CVPR workshop.
Research community
Helped organise the Machine Learning Summer School in Kraków and the ELLIS Doctoral Symposium on Robust AI.
Curriculum vitae
CVs
Two concise views of my experience, tailored to research and engineering contexts.
Research CVPublications, research experience, and academic serviceEngineering CVTechnical experience, projects, and systems work
Updated September 2026