Mitko Veta

Mitko Veta is an Associate Professor in the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), specializing in medical image analysis. His research focuses on developing deep learning methods for histopathology image analysis to enhance diagnostic accuracy and reduce pathologist workload. He leads the Medical Image Analysis group, contributing to automated quantitative tools for pathology reporting and treatment planning.

Academic Background: Veta earned his M.Sc. in Electrical Engineering from Ss. Cyril and Methodius University (Macedonia, 2009), followed by a Ph.D. in histopathology image analysis at University Medical Center Utrecht (2014). He joined TU/e as a postdoc in 2014 and became an assistant professor in 2016, advancing to his current role in 2021.

Research Interests: His work spans histopathology image analysis, deep learning, domain adaptation, and applications in oncology (e.g., breast cancer, melanoma). He develops algorithms for mitosis detection, tumor-infiltrating lymphocyte assessment, and AI-driven clinical decision support. Key contributions include the MIDOG++ dataset and the LYSTO benchmark.

Projects: He co-leads the Spectralligence AI project (2021–2024), focusing on AI-driven medical imaging solutions. His research addresses clinical challenges like myocardial scar quantification and checkpoint inhibitor treatment outcomes.

Teaching: Veta teaches courses such as Machine Learning in Medical Imaging and Biology and AI for Medical Image Analysis, emphasizing practical applications of AI in healthcare.