Yaroslav Prytula
I am interested in solid theoretical and algorithmic foundations for learning and computational decision-making under imperfect information. To achieve that, I combine techniques from machine learning, optimization, and statistics.
My research focuses on instance-aware segmentation, transformer-based models, and biomedical imaging, with an emphasis on robustness and overlapping objects.
Some current research interests
Medical Computer Vision
Query-based and transformer-driven segmentation models for overlapping objects in biomedical images.
Publications on this topic:
@InProceedings{Prytula_2025_CVPR,
author = {Prytula, Yaroslav and Tsiporenko, Illia and Zeynalli, Ali and Fishman, Dmytro},
title = {IAUNet: Instance-Aware U-Net},
booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR) Workshops},
month = {June},
year = {2025},
pages = {4739--4748}
}