Professor Emiliano Spezi’s research combines medical physics, biomedical engineering and data science to develop methods for medical imaging, the study of biological tissues and personalized healthcare. His early work focused on Monte Carlo simulation of radiation transport, dose calculation and radiotherapy verification, informed by clinical practice in Italy and the UK. This developed into research on image-guided treatment planning, molecular radiotherapy dosimetry and automated image segmentation.
His research subsequently expanded into quantitative medical imaging and radiomics, investigating how information extracted from medical imaging scans can characterize tissue and predict clinical outcomes. This work emphasizes reproducible measurements, independent validation of predictive models and software that supports consistent analysis across institutions.
His most recent interests extend beyond oncology to the integration of imaging, pathology, genomics and clinical information for studying tissue microstructure, biological variability and disease processes. Current work explores non-invasive imaging biomarkers, interpretable machine learning and deep learning, alongside federated approaches that enable collaborative research across institutions. These interests retain a focus on reliable computational methods and their practical use in biomedical research and clinical decision-making.
Professor Spezi trained in physics and medical physics at the University of Bologna and holds a PhD from the University of Wales College of Medicine in Cardiff. His career spans clinical practice in medical physics with engineering research and academic leadership.
