Ing. Michal Průšek

Michal Průšek received his B.Sc. degree in Mathematical Informatics from the Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, in 2023, with a thesis on gesture-controlled drones, and his M.Sc. degree in Applied Mathematical Stochastic Methods from the same faculty in 2026, with a thesis on biomedical image segmentation. He is currently pursuing his Ph.D. degree at the same faculty under the supervision of Adam Novozámský and Filip Šroubek, while working as a researcher at the Institute of Information Theory and Automation of the Czech Academy of Sciences (ÚTIA AV ČR). His research focuses on label-efficient deep learning for biomedical microscopy, spanning segmentation, phenotyping, and morphometric analysis, with a secondary interest in retrieval-augmented generation and Bayesian optimization in latent spaces. He is the author of the SpheroSeg and MAPtimize platforms, which are used by several international laboratories, and collaborates with UCT Prague, BIOCEV, and Institut Curie in Orsay, France, where he completed a research stay in 2026.