Prof. Victor Chang
Federated learning as a route to cross-border health data reuse without data movement; validating clinical AI outside the lab; secure-by-design health data infrastructure.
Name: Prof. Victor Chang
Title: Professor of Applied AI and Business Analytics
Affiliation: Department of Business Analytics and Information Systems, Aston Business School, Aston University, Birmingham, UK
Country: United Kingdom
Expertise tags: Healthcare AI · Federated learning & privacy-preserving analytics · Internet of Medical Things · Health data governance · Cybersecurity · Generative AI/LLMs
Victor Chang is Professor of Applied AI and Business Analytics at Aston Business School, Aston University, a post he has held since May 2022 after serving as Professor of Data Science and Information Systems at Teesside University. He holds a PhD in Computer Science from the University of Southampton, an MPhil from Cambridge, an MBA in Technology Management, and degrees in telecommunications engineering and physics from the University of Sydney.
His research sits at the intersection of health data and trustworthy AI: privacy-preserving and federated learning, Internet of Medical Things architectures, e-diagnosis systems for diabetes, breast cancer and cardiovascular disease, and knowledge-graph-driven clinical consultation systems. A UK–Japan 6G collaboration with the University of Tokyo, funded by the International Science Partnerships Fund, produced federated detection models reaching 96.8% accuracy without data leaving the originating device.
He has published over 300 peer-reviewed papers, given 57 international keynotes, and ranks in the global top 2% of cited scientists. Recognitions include Data Leader of the Year 2025 at the British Data Awards, Cybersecurity Professional of the Year 2026, Data Scientist of the Year 2026 at Computing's AI and Software Development Awards, and a place on Computing's AI Leadership Index 2026 as the only academic among 25 listees. He is Editor-in-Chief of IJOCI and OJBD and founding chair of the IoTBDS, COMPLEXIS and FEMIB conferences.
Links: Aston profile · Google Scholar · LinkedIn
ORCID 0000-0002-8012-5852
