Showcasing AI Innovation: Masaryk University at Research Data Day 2025
Representatives of Masaryk University actively participated in the Research Data Day and EOSC National Tripartite Event, held in Brno on May 21–22, 2025 under the auspices of EOSC CZ. The national conference focused on the development of the European Open Science Cloud (EOSC) and explored the evolving role of research infrastructures, data, and artificial intelligence (AI) in today’s scientific ecosystem.
On Thursday, May 22, the program turned its focus toward the application of artificial intelligence in research and scientific infrastructures. Within the session titled Practical Examples and Future Directions of Data, AI and EOSC, AI-focused talks from Masaryk University drew particular attention.
Tomáš Brázdil, from the Institute of Information Theory and Automation at the Faculty of Informatics, presented a talk entitled “Digital Pathology Using Artificial Intelligence in Practice.” His presentation explored how neural networks are being used in real-world healthcare environments to analyze digital pathology images, identify abnormalities, and support diagnostic decision-making.
Saltuk Eyrilmez, a researcher at CEITEC Masaryk University, introduced his work on “Quantum Mechanics-Enhanced Data Generation for ML-Driven Drug Discovery.” Eyrilmez demonstrated how quantum mechanical simulations can generate highly accurate molecular data, which are then used to train machine learning models for predicting bioactivity — offering new avenues in AI-powered drug discovery.
High-Level Contributions with European Reach
The AI session also featured Vladimír Ulman, a researcher at IT4Innovations in Ostrava and at the Centre for Biomedical Image Analysis at the Faculty of Informatics, Masaryk University, who presented the MIFA initiative (Metadata, Incentives, Formats, and Accessibility). This project aims to improve the reproducibility and reusability of datasets in bioimage analysis, laying the groundwork for more robust AI training and greater scientific integrity.
Ulman emphasized the crucial importance of data quality in AI: “Artificial intelligence is only as useful as the data it learns from. FAIR data – especially in bioimage analysis – are essential to ensuring that AI results can be trusted, reproduced, and scaled across labs and borders.”
Masaryk University played a prominent role not only as one of the organizing institutions but also through its strong presence among keynote speakers and experts contributing to thematic sessions across the conference agenda.
For more information about the conference, visit the official EOSC CZ website.
“Artificial intelligence is only as useful as the data it learns from.”
Vladimír Ulman
