Short Bio

Daniele Ravì is an Associate Professor in Computer Science at the University of Messina, specialised in artificial intelligence, medical imaging, and disease progression modelling. He holds honorary appointments at University College London. His career includes a PhD in Computer Vision (University of Catania), visiting research at the University of Surrey, and posts at Imperial College London and University College London.

His research focuses on clinical AI – including generative models for neurological disease, MRI and imaging biomarkers, early diagnosis, image-guided surgery, and smart sensors for health monitoring. He has published in leading venues (Medical Image Analysis, IEEE Transactions on Medical Imaging, NeuroImage), secured over €500,000 in competitive grants, and coordinated multi-disciplinary teams bridging academia and industry.

Daniele has received several awards, most notably the Best Paper Award at Medical Image Analysis 2025, a prestigious prize won by only a handful of labs worldwide. He is an invited keynote speaker (i.e. TEDx), organiser of international conferences, and active in editorial/program committees and serves in editorial and reviewing leadership roles, including Associate Editor for Pattern Recognition and IEEE Engineering in Medicine and Biology Society (EMBS), and Area Chair for MICCAI.

As a supervisor and educator, he trains PhD and MSc students, delivers modules in AI and data science, and serves as examiner across Europe. His technology transfer and industry experience includes digital health startups, hyperspectral brain imaging, and translation of algorithms from research to clinical and business use.

Passionately engaged in international networking, outreach, and mentoring, Daniele supports research community growth in medical AI and digital health innovation.

Recent News

• Best Paper Award at Medical Image Analysis (MedIA), 2025. This is one of the most prestigious recognitions in the field, awarded annually only to a select few leading international labs.

Selected Recent Publications

• Brain latent progression: Individual-based spatiotemporal disease progression on 3D brain MRIs via latent diffusion, MedIA, 2025
• An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training, MedIA, 2024
• Degenerative adversarial neuroimage nets for brain scan simulations: Application in ageing and dementia, MedIA, 2022
• Augmenting Dementia Cognitive Assessment with Instruction-less Eye-tracking Tests, IEEE JBHI, 2020

See my Google Scholar profile for the full publication list.

Modules Taught

• Programming (BSc Computer Science, Module Leader) — University of Messina
• Data Mining Analytics (BSc Computer Science, Module Leader) — University of Messina
• Big Data Acquisition (MSc Data Science, Module Leader) — University of Messina
• Informatics (School of Specialisation at the Medicine Department) — University of Messina