معرفی
Vincenzo Della Mea is an Associate Professor of Information Processing Systems at the University of Udine's Department of Mathematical, Computer and Physical Sciences. His research focuses on medical informatics, digital pathology, biomedical ontologies, and AI applications in healthcare. He holds abilitation to full professorship and is a member of the WHO Italian Collaborating Centre for International Classifications (WHO-FIC), ICHI Task Force, and ESDIP's Executive Board. He leads the EU MSCA Doctoral Network BosomShield (2022-2026) and previously managed the AIDPATH Marie Curie project. As an editor for journals like Digital Health and Journal of Pathology Informatics, he bridges academia and practice. Beyond academia, he is a poet with awards, including the Nelle terre dei Pallavicino Prize for his 2004 collection Algoritmi, and organizes interdisciplinary events merging science and literature.
Education & Roles: Holds a professorship in Computer Science and teaches courses on web technologies, medical informatics, and AI across multiple degree programs. Previously served as Vice-President of SIBIM (Italian Biomedical Informatics Society).
Research Interests: Specializes in digital pathology, medical AI, telemedicine, and standardization of health classifications like ICD-11 and ICF. His work emphasizes ontology harmonization and machine learning for clinical decision support.
Recent Contributions: Published on WHO classification harmonization, AI-driven pathology tools, and energy-sector LLM applications. Active in editorial roles and international collaborations, including the HEROHE Challenge for breast cancer analysis.
Awards & Recognition:
- 2023 – Poetry collection Clone 2.0 (neurally generated)
- 2005 – Nelle terre dei Pallavicino Award
Grants & Projects: Led EU-funded projects (AIDPATH, BosomShield) and contributed to initiatives like the ICD-11 Mortality Coding System. Collaborates with institutions like AcegasApsAmga on AI for utilities.
Labs & Initiatives: Involved in digital pathology workflow optimization and educational platforms for medical coding and AI ethics.
