Professional Background
Accomplished Data and AI Governance leader with over 20 years of experience across HKSTP, HKMA, and HKEX. Specializes in AI adoption, AI governance, use case development, and data governance, with extensive experience in emerging technologies and regulatory environments. Proven track record in helping organizations translate AI opportunities into responsible, practical applications through governance frameworks, use case training, and enterprise data initiatives.
Project Highlights
AI Adoption, Governance & Use Case Enablement
- Scope
- Developed AI adoption and governance approaches to help organizations identify, assess, and prioritize practical AI use cases, supported by training for business and technology teams.
- Key Outcome
- Enabled teams to move beyond AI experimentation with clearer governance, stronger use case awareness, and a structured approach to responsible AI adoption.
Hong Kong & Shenzhen Cross-Border Data Verification Platform (DLT & DID)
- Scope
- Spearheaded the data architecture for a cross-border data verification platform in collaboration with HKMA, leveraging DLT nodes and DID protocols.
- Key Outcome
- Enabled privacy-preserving, tamper-proof verification across participating institutions without centralizing sensitive data, establishing a foundation for trusted cross-border data exchange.
Cross-Industry Federated Learning & Privacy Platform
- Scope
- Architected and deployed a Privacy-Preserving Computation framework using Federated Learning across insurance and healthcare data environments.
- Key Outcome
- Enabled cross-domain AI and analytics without transferring raw customer data from native environments, demonstrating how advanced AI applications can operate under stringent privacy requirements.
HKMA Interbank Account Data Sharing (IADS)
- Scope
- Supported data standardization architecture and stakeholder coordination for the IADS initiative across 29 participating banks in Hong Kong.
- Key Outcome
- Helped establish unified data definitions and customer-consented data-sharing foundations, strengthening the data infrastructure required for future analytics, automation, and AI adoption.
Specialized Areas
- AI Adoption & Use Case Development
- AI Governance, Risk & Responsible AI
- AI Use Case Training & Workforce Enablement
- Data Governance, Privacy & Regulatory Compliance
- Emerging Technology & Data Architecture
Academic Qualifications
- CDMP Master — Certified Data Management Professional (Master Level, DAMA)
- AIGP — Certified AI Governance Professional (IAPP)
- CIPP/E — Certified Information Privacy Professional/Europe (IAPP)
- PMI-PMP & PMI-ACP — Project Management Professional & Agile Certified Practitioner
- Lean Six Sigma Black Belt — Process Optimization & Quality Management
- CISSP — Certified Information Systems Security Professional
- PMI-CPMAI — Certified Professional in Managing AI