Synthetic Health Data Education and Training Masterclass Series

Opportunity

Led by La Trobe University with support from the DHCRC Synthetic Data (SynD) Community of Practice and international experts from Swansea University and the Secure Anonymised Information Linkage (SAIL) Databank, this series addresses critical barriers in health data access, privacy, and interoperability. Participants gain hands-on experience with AI-enhanced low- and high-fidelity synthetic data, explore federated AI models for multi-site analysis, and understand ethical, regulatory, and governance considerations. The program demonstrates how AI and synthetic data together can accelerate adoption of Common Data Models (CDMs) such as OMOP, enhance predictive analytics, and support innovation while maintaining trust, privacy, and social license.

Project Objectives

A targeted education, training, and masterclass series on synthetic health data and AI-driven analytics, designed to equip participants with the skills, knowledge, and confidence to generate, manipulate, and analyse synthetic datasets responsibly and effectively in healthcare research, education, and innovation. The program integrates AI techniques for synthetic data generation, federated learning, and distributed analytics, alongside real-world applications, governance considerations, and stakeholder engagement, to build practical capability and translational expertise for privacy-preserving, data-driven health innovation. This event will be held in May-June 2026 across Australian states and territories.