Dimitrios Theodoropoulos is a researcher and AI specialist in medical imaging with expertise in machine learning, deep learning, computer vision, and artificial intelligence applications in healthcare, particularly in radiology and diabetic retinopathy analysis. He is currently pursuing a PhD in Artificial Intelligence in Medical Imaging at the University of Crete, Medical School, building on a master’s degree in computer engineering from Hellenic Mediterranean University and a bachelor’s degree in physics with specialization in microelectronics from the University of Crete, complemented by training as a radiology assistant. Alongside his academic path, he has worked extensively as a radiographer in MRI, CT, X-ray, mammography, DEXA, and EEG imaging, effectively integrating research with clinical practice. He has served as a visiting research fellow at FORTH-CBML and collaborated with institutions such as the Athens Neurotraining Center and Alexandra Hospital, bridging advanced AI research with healthcare innovation. His research focuses on the development of machine learning and deep learning algorithms for classification, segmentation, and detection tasks in medical imaging, with emphasis on diabetic retinopathy, intensive care monitoring, and noninvasive intracranial pressure assessment, while also extending to areas such as pollen analysis. He has published widely in Scopus-indexed journals and conferences, presented at international congresses and academic symposiums, and delivered guest lectures at the National and Kapodistrian University of Athens. Proficient in Python, MATLAB, TensorFlow, PyTorch, Scikit-learn, Linux, and Docker, he has advanced expertise in data preprocessing, model optimization, and AI-driven biomedical solutions. With certifications in Python programming, machine learning, and deep learning, combined with memberships in the Hellenic Artificial Intelligence Society and the Union of Greek Physicists, he demonstrates a rare integration of technical, clinical, and analytical skills, enabling him to advance scientific progress while contributing to patient-centered healthcare innovation.