Biography
- Chair Professor of Computational Intelligence in Department of Data Science and Artificial Intelligence at The Hong Kong Polytechnic University
- Research focuses on data science and artificial intelligence, particularly in the areas of machine learning, evolutionary computation, and big data analytics
- SRFS project — aims to develop an integrated intelligent healthcare system that adapts generalist AI models into specialist medical imaging models. The system will enable visual question answering, automated radiology report generation, and computer-aided diagnosis. This research will enhance healthcare quality, ease resource pressures, and strengthen Hong Kong’s leadership in AI-driven healthcare innovation.
- Awards and Honours:
- RGC Senior Research Fellow (2025)
- IEEE CIS Evolutionary Computation Pioneer Award (2026)
- IEEE Computational Intelligence Magazine Outstanding Paper Award (2024)
- IEEE Transactions on Cybernetics Outstanding Paper Award (2020)
- IEEE Transactions on Neural Networks and Learning Systems Outstanding Paper Award (2016)
Project Title
- Towards Adaptive Pretrained Vision-Language Foundation Models for Medical Image Analysis
Award Citation
Professor Kay Chen TAN, Head of the Department of Data Science and Artificial Intelligence and Chair Professor of Computational Intelligence at The Hong Kong Polytechnic University, is an IEEE Fellow and a world-renowned expert in AI, evolutionary computation, and machine learning. His global influence is underscored by his recognition as a "Highly Cited Researcher 2024" by Clarivate and as the recipient of the 2026 IEEE CIS Evolutionary Computation Pioneer Award. He has co-authored over 400 peer-reviewed articles, with over 35,000 citations on Google Scholar.
Professor Tan has been awarded the RGC Senior Research Fellow for his project, “Towards Adaptive Pretrained Vision-Language Foundation Models for Medical Image Analysis.” This pioneering research aims to build an integrated intelligent healthcare system to deliver personalized, human-centric healthcare service by adapting large-scale, generalist AI models into highly accurate specialist models for medical imaging. It will enable advanced functionalities, such as visual question answering, automated radiology report generation, and computer-aided diagnosis. The project will build a robust and scalable framework, pioneering data-efficient and privacy-preserving methodologies, and creating clinical applications that are practical, interpretable, and widely generalizable.
This fellowship honors Professor Tan's outstanding leadership and contributions. His work is poised to enhance the healthcare quality and efficiency, alleviate the immense burden on medical resources, and solidify Hong Kong’s leadership in AI-powered healthcare innovation. By advancing the applications of trustworthy AI, this research will ultimately transform patient care and create a lasting impact on the diagnosis and management of complex diseases.
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