Digital Health CRC · La Trobe University · University of Sydney
The Trusted Synthetic Health Data & Federated Analytics Masterclass brings together researchers, policymakers, data custodians, clinicians, and technical experts to build shared capability in the responsible use of synthetic health data. The series responds to growing demand for safe, ethical, and practical ways to accelerate data-driven health innovation while maintaining public trust.
Across the program, participants explore how synthetic data can be used to prototype analyses, test pipelines, and support workforce development without exposing sensitive real-world data. The masterclasses focus on understanding when synthetic data is appropriate, and how trade-offs between data utility and privacy can be navigated with confidence.
A strong emphasis is placed on governance, ethics, and social licence. Participants engage with contemporary governance frameworks, privacy-preserving analytics, and federated data ecosystem models that enable collaboration across institutions and jurisdictions.
Delivered in partnership with leading Australian universities and international experts from Swansea University and the SAIL Databank, the series is designed to strengthen cross-sector dialogue and equip participants with insights they can apply directly in research, policy, and service settings.
Join national and international experts for a two-day masterclass designed to accelerate Australia's capability in synthetic health data, privacy-preserving analytics, and federated data ecosystems.
Building a clear, shared understanding of what synthetic health data is — and how to use it responsibly.
Technical hands-on, expert demonstrations, and social licence pathways for real-world implementation.
The Masterclass Series brings together professionals from across the health data ecosystem who are ready to build practical capability in synthetic data, privacy, and governance.
This masterclass series gave our team a shared vocabulary and a practical framework for thinking about synthetic data — something we had been struggling to articulate for months. The combination of international expertise and Australian context was exactly what we needed.
