The MBAI Consortium exists to strengthen collaboration across organisations, accelerate the adoption of AI-enabled approaches, build capability, and support the development of shared infrastructure, frameworks and partnerships that enhance research and healthcare outcomes.
The Consortium seeks to position Melbourne as a nationally and internationally recognised leader in biomedical AI by fostering collaboration, innovation and responsible practice across the research and health ecosystem.
AI Research Capability
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Training and Events
Browse AI training offerings, upcoming events and recorded webinars delivered by MACH partners.
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Research AI Sandbox
The University of Melbourne, in partnership with precinct research institutes and health partners, is pleased to announce the launch of the Research AI Sandbox
AI Research Impact
Explore these examples of successful research impact from across the MACH partnership, translating complex science into powerful stories of discovery and hope using AI.
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AI-Accelerated Drug Discovery
Showcasing WEHI’s use of generative AI to design novel therapeutics at unprecedented speed.
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Australian Epilepsy Project (AEP)
A national AI-enabled brain-health platform translating 30+ years of Florey research in imaging, genetics and psychology into patient outcomes
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Baby Moves
Applying AI to smartphone videos to enable early, accessible detection of cerebral palsy led by MCRI.
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Developing 3D Spatial Models of Cancer
This Peter MacCallum Cancer Centre project uses deep learning and computer vision to extrapolate 2D spatial-omics information from tissue sections into faithful 3D in silico representations of tumours.
About MBAI Activities
The Consortium’s activities focus on developing shared infrastructure and services, building workforce capability through training and communities of practice, strengthening collaboration between researchers and clinicians, and establishing governance, privacy and data-stewardship frameworks that support multi-institutional work while preserving institutional autonomy and data sovereignty.
Current initiatives include the University of Melbourne’s Research AI Sandbox, which provides a governed environment for researchers to explore advanced AI models and workflows while generating evidence about research value, cost, security and capability needs. The Consortium is also developing a longer-term vision for the precinct as a connected biomedical discovery and validation ecosystem – linking computational analysis with distributed data, laboratories, clinical environments, cohorts and translational pathways.
The Consortium also supports joint research, infrastructure and funding opportunities and engagement with government, industry and national research infrastructure. Its aim is to position Melbourne as a nationally and internationally recognised leader in responsible biomedical AI.
Objectives
- Infrastructure and Capability: Develop and promote shared biomedical AI research infrastructure, services and capability across member organisations
- Workforce Development: Build AI capability through collaborative training, shared resources and communities of practice
- Clinical and Research Integration: Foster collaboration between research organisations, health services and clinical leaders to support the application of AI in research and healthcare
- Governance and Collaboration: Promote best-practice governance, ethics, privacy and data stewardship, and support frameworks that enable multi-institutional collaboration
- Strategic Engagement: Pursue collaborative research, infrastructure and funding opportunities; engage with government, industry and the broader biomedical innovation ecosystem; and promote the Consortium’s activities, capabilities and achievements through shared communications and outreach
The University of Melbourne
AI at the University of Melbourne
Centre for Digital Transformation of Health
Melbourne Connect – AI Hub for Innovations
Melbourne Data Analytics Platform
The Centre for Artificial Intelligence and Digital Ethics
Research AI in the Faculty of MDHS
La Trobe University
Australian Centre for AI in Medical Innovation (ACAMI)
WEHI
AI and Machine Learning at WEHI