About the Conference
Connecting exposomics, infectious-disease intelligence, medical AI, and trusted health-data research.
Welcome Message from the Conference Chair
Dear Colleagues and Distinguished Guests,
Welcome to the International Conference on Public Health and AI 2026 at Macau University of Science and Technology.
This conference brings together researchers, clinicians, public health experts, and international collaborators to explore emerging challenges and future opportunities in public health and artificial intelligence. The programme focuses on three key themes: Bridging Classical Toxicology and Exposomics, Respiratory Epidemic AI, and Public Health Data Governance and Trusted Research Environments (TRE).
Through nine keynote presentations, three invited talks, and a cross-track roundtable, we aim to connect environmental and genomic evidence with infectious-disease intelligence, real-world medical AI, and secure health-data research.
On behalf of the Organizing Committee, I would like to sincerely thank all speakers, participants, and collaborating institutions for their support and contributions. We hope this conference will serve as a valuable platform for scientific exchange and future cooperation.
We wish you a productive and enjoyable conference in Macao.
Prof. Chitin Hon
Conference General Chair
Conference Overview
ICPHAi Macao 2026 — the First International Conference on Public Health and AI — is an international academic conference bringing together researchers, clinicians, public health professionals, AI scientists, data governance specialists, and policy stakeholders from across the world.
Hosted by the Faculty of Innovation Engineering at Macau University of Science and Technology, and co-organised by the HKU-Pasteur Research Pole at The University of Hong Kong, the conference will be held on 22 September 2026 in Taipa, Macao, China.
The single-day programme is structured around three integrated tracks: toxicology and exposomics, respiratory epidemic AI, and public health data governance and trusted research environments. Together, the sessions move from exposure and disease evidence to real-world AI performance, medical innovation, and responsible data use.
Conference Objectives
Integrate evidence across exposomics, infectious diseases, clinical research, and public health AI
Connect environmental, clinical, and population data with fit-for-purpose AI methods
Advance exposure-to-disease research through spatial, genomic, and toxicological evidence
Improve epidemic preparedness through emerging-disease intelligence and robust real-world classification
Promote trusted research environments and responsible health-data governance
Turn cross-disciplinary scientific exchange into durable international collaboration
Why This Conference Matters
Exposure and Disease
Spatial, molecular, and genomic evidence can reveal how environmental exposures shape disease risk and inequity.
Real-World AI
Useful health AI depends on representative training data, rigorous validation, and clinically meaningful deployment.
Emerging Infections
Animal–human transmission and respiratory threats require coordinated intelligence across disciplines and borders.
Trusted Data Use
Secure research environments and responsible governance enable collaboration while protecting sensitive health data.
Host Institutions
Lead Host Organizer
Faculty of Innovation Engineering
Macau University of Science and Technology
Co-Organizer
HKU-Pasteur Research Pole, LKS Faculty of Medicine
The University of Hong Kong
Conference Highlights
Nine Keynotes
A full-day sequence of keynote presentations spanning all three conference tracks.
Three Invited Talks
Focused perspectives on medical AI, infectious disease, and data-intensive health research.
Three Thematic Tracks
Exposomics, respiratory epidemic AI, and public health data governance in one integrated programme.
Cross-Track Roundtable
A one-hour discussion on collaboration priorities and future directions.
Delegate Networking
A networking lunch and farewell dinner supporting international exchange.