About
Aleksei Tiulpin is a Visiting Professor affiliated with the Department of Electrical Engineering and Automation and Sensor Informatics and Medical Technology. His research focuses on applying machine learning and deep learning to medical imaging and biomedical engineering, particularly for osteoarthritis diagnosis and progression prediction.
His work includes automating histopathological grading using micro-CT, multi-modal imaging data fusion, and segmentation of chest X-rays. Recent publications highlight trends in Bayesian decision-making, tidemark segmentation, and clinical decision support systems.
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