Michael Reiter

Michael Reiter is a Senior Lecturer at the Institute of Visual Computing & Human-Centered Technology, part of the Faculty of Informatics at TU Wien. His research focuses on Machine Learning, Pattern Recognition, and Computer Vision, particularly in medical applications such as flow cytometry data analysis for leukemia diagnosis and minimal residual disease (MRD) assessment. He leads the MyeFLOW project (2020–2025), which develops automated methods for immunophenotyping and MRD detection in pediatric leukemia. His work bridges machine learning and clinical diagnostics, emphasizing explainable AI in healthcare.

Reiter collaborates with medical institutions to translate algorithms into clinical tools, such as the FlowMe decision support system. His research interests include transformer networks, UMAP visualization, and Gaussian mixture models for biomedical data. He has supervised diploma theses on topics like meta learning for blast cell classification and U-Net-based flow cytometry analysis.

Reiter’s publications span over two decades, with recent emphasis on medical AI applications. His lab, the Computer Vision Lab, focuses on visual computing for healthcare, robotics, and cultural heritage digitization. Current projects address automated analysis of museum herbarium collections and empathic robotic systems for autism therapy.