The International Workshop on Large AI Models for Biomedicine (LAI4BM 2025) successfully concluded on July 12, 2025, at the HKUST Jockey Club Institute for Advanced Study. This groundbreaking workshop brought together leading researchers, practitioners, and innovators from around the world to explore the latest advancements in Large AI Models for Biomedical Applications.

Workshop Overview

The LAI4BM 2025 Workshop focused on cutting-edge AI technologies, machine learning techniques, and their transformative applications in healthcare, medical research, and biomedical data analysis. Through keynote presentations, technical sessions, and interactive panel discussions, attendees gained valuable insights into the latest developments in AI-driven biomedical research.

The event successfully fostered collaboration between AI researchers and biomedical professionals, accelerating innovation in healthcare technology and medical AI applications. The workshop featured distinguished speakers from prestigious institutions including Harvard University, Stanford University, Imperial College London, and leading healthcare organizations.

Distinguished Speakers and Their Contributions

The workshop featured an impressive lineup of international experts who shared their cutting-edge research and insights:

Morning Session Highlights

Prof. Pranav Rajpurkar from Harvard University delivered a compelling keynote on “Beyond Assistance: Rethinking AI-Human Integration in Radiology,” exploring how AI can transform medical imaging beyond simple assistance tools.

Prof. Ruijiang Li from Stanford University presented “Multi-modal Foundation AI for Precision Oncology,” discussing the integration of multiple data modalities for personalized cancer treatment.

Mr. Dennis Lee from Hong Kong Hospital Authority shared practical insights on “Reimagining Healthcare with AI: A Real-World Application of Clinical Management Systems in Hong Kong Hospital Authority,” providing valuable real-world implementation perspectives.

Prof. Dong Liang from SIAT, Chinese Academy of Sciences, presented “Magnetic Resonance Live imaging: from Photograph to Videography,” showcasing advances in real-time medical imaging.

Prof. Kyongtae Tyler Bae from The University of Hong Kong discussed “Clinical Implementation of AI in Radiology,” addressing practical challenges and solutions in clinical deployment.

Afternoon Session Highlights

Prof. Xiaomin Ouyang from HKUST presented “Building Foundation Model-Powered Multimodal Sensing Systems for Daily Healthcare,” exploring AI applications in everyday health monitoring.

Prof. Cheong Kin Ronald Chan from CUHK & Hong Kong Hospital Authority delivered an insightful talk on “What Doctors Think, Want and Fear About the Large AI Model?” providing crucial clinical perspectives.

Prof. Zheng Li from CUHK showcased “Intelligent Surgical Assistive Robots,” demonstrating the future of AI-powered surgical assistance.

Prof. Xin Wang from CUHK presented “Deep Learning Models for Cancer Subtype Classification to Advance Precision Oncology,” highlighting AI’s role in personalized cancer treatment.

Dr. Yang Cheng from AstraZeneca shared industry insights on “Charting the AI Pathway: Opportunities and Challenges in Pharma Development.”

Prof. Chen Qin from Imperial College London concluded with “Artificial Intelligence Meets Medical Imaging: From Signals to Interpretation,” bridging technical innovation with clinical application.

Panel Discussions: Addressing Critical Questions

The workshop featured two thought-provoking panel discussions moderated by Prof. Hao Chen:

1. “Are We There for Deploying Large AI Models in Biomedical Applications?” - This morning panel explored the current readiness and challenges in implementing large AI models in clinical settings.

2. “How Will Large AI Models Reshape the Future of Biomedicine?” - The afternoon panel discussed future directions and transformative potential of AI in healthcare.

These discussions provided valuable insights into both the opportunities and challenges facing the field, fostering meaningful dialogue between researchers, clinicians, and industry professionals.

Organizing Excellence

The workshop was expertly organized by a distinguished committee of HKUST faculty members:

• Prof. Hao Chen - Assistant Professor of CSE, CBE and LIFS, HKUST
• Prof. Jiguang Wang - Padma Harilela Associate Professor of CBE and LIFS, HKUST
• Prof. Kai Liu - Cheng Professor of Life Science, HKUST
• Prof. Yingcong Chen - Assistant Professor at AI Thrust, Information Hub of HKUST (GZ)
• Prof. Can Yang - Dr Tai-chin Lo Associate Professor of Mathematics, HKUST
• Prof. Xiaofang Zhou - Otto Poon Professor of Engineering & Chair Professor of CSE, HKUST

Supporting Organizations

The workshop was supported by several key organizations:

• HKUST Collaborative Center for Medical and Engineering Innovation
• State Key Laboratory of Nervous System Disorders
• Center for Medical Imaging and Analysis
• Department of Computer Science and Engineering, HKUST
• Department of Chemical and Biological Engineering, HKUST
• The Hong Kong University of Science and Technology (HKUST)

Workshop Impact and Success

Workshop participants and speakers gathered for group photo

The workshop successfully achieved its objectives of:

• Bringing together leading experts from academia, industry, and healthcare
• Facilitating knowledge exchange on the latest AI developments in biomedicine
• Fostering collaborations between AI researchers and biomedical professionals
• Addressing practical challenges in deploying AI solutions in healthcare settings
• Exploring future directions for AI in biomedical applications

Looking Forward

The LAI4BM 2025 Workshop has set a strong foundation for continued collaboration and innovation in the field of AI for biomedicine. The insights shared, connections made, and discussions held during this event will undoubtedly contribute to advancing the field and improving healthcare outcomes through AI technology.

The organizers extend their heartfelt gratitude to all speakers, attendees, and sponsors who made this workshop a tremendous success. The enthusiasm and engagement demonstrated by all participants highlight the bright future ahead for AI applications in biomedicine.

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The LAI4BM 2025 Workshop was organized by the HKUST SMART Lab and supported by various departments and centers at The Hong Kong University of Science and Technology.

About Smart Lab

Smart Lab, led by Prof. Hao Chen, is committed to pushing the boundaries of trustworthy AI technologies for healthcare and science. Our research directions include large-scale models for healthcare, computer-assisted intervention, AI for science, and bioinformatics, etc. Our ultimate goal is to spearhead a transformative revolution in medical practices and scientific discoveries, paving the way for a brighter and healthier future.

About The Hong Kong University of Science and Technology

The Hong Kong University of Science and Technology (HKUST) is a world-class university that excels in driving innovative education, research excellence, and impactful knowledge transfer. With a holistic and interdisciplinary pedagogy approach, HKUST was ranked 3rd in the Times Higher Education’s Young University Rankings 2024, while 12 of its subjects were ranked among the world’s top 50 in the QS World University Rankings by Subject 2024, with “Data Science and Artificial Intelligence” being ranked first in Hong Kong and 10th in the world. Our graduates are highly competitive, consistently ranking among the world’s top 30 most sought-after employees. In terms of research and entrepreneurship, over 80% of our work was rated “internationally excellent” or “world leading” in the latest Research Assessment Exercise 2020 of Hong Kong’s University Grants Committee. As of October 2024, HKUST members have founded over 1,800 active start-ups, including 10 Unicorns and 14 exits (IPO or M&A).