The RAIsE Model

The RAIsE Model

RAIsE

RAIsE operates through an integrated model that connects interdisciplinary education, applied research, and industry collaboration to advance responsible AI capability and impact.

AI Education

RAIsE advances interdisciplinary AI education designed to equip students across RMIT’s three colleges — STEM, Business and Law, and Design and Social Context — with practical, responsible AI capability.

The Hub supports the development of industry-informed learning pathways that move beyond technical specialisation to build AI literacy, applied problem-solving skills, and ethical understanding. From foundational AI awareness to applied industry projects, RAIsE prepares students to work confidently and responsibly with AI across diverse professional contexts.

A flagship initiative of the Hub is the Artificial Intelligence in Practice minor, co-designed and developed in collaboration with strategic industry partners, including Microsoft. The minor enables students from a broad range of disciplines to understand, apply, and critically engage with AI technologies in real-world settings.

Through curriculum innovation, co-design workshops, and industry engagement, RAIsE strengthens RMIT’s commitment to developing AI-ready graduates across the University.

Student Community & Engagement

RAIsE is also building an interdisciplinary AI student community to complement formal learning pathways. Through student-led initiatives, peer engagement, and collaboration with academic and industry mentors, the Hub creates spaces for students to explore, apply, and discuss AI beyond the classroom.

These initiatives strengthen pathways between learning, experimentation, and real-world impact.

Research & Innovation

RAIsE advances interdisciplinary, problem-driven AI research aligned with national and societal priorities.

Rather than operating as a standalone research centre, RAIsE enables cross-cutting AI capability that connects discipline-led excellence with applied innovation and translation pathways. The Hub strengthens coordination, visibility, and scale across domains — supporting researchers to translate AI expertise into real-world impact.

RAIsE’s research themes serve as strategic entry points for applying AI capability at scale across sectors, while remaining responsive to emerging industry and community needs. Current focus areas include:

  • AI for Future-Ready Manufacturing
  • AI for Sustainable Health Systems
  • AI for Safe and Trusted Public Services

Across these domains, RAIsE supports collaborative research that integrates technical innovation with domain expertise, responsible AI practice, and pathways to application.

By bridging research, education, and industry engagement, RAIsE enhances RMIT’s capacity to deliver AI innovation that is interdisciplinary, applied, and impact-driven.

Student Community & Engagement

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Develops a non-destructive, μ-CT image-based technique to assess the integrity of self-piercing rivets (SPR), which are increasingly used in automotive manufacturing. Combines deep learning with advanced image processing to replace manual, destructive, and costly inspection methods.
 → Improving quality assurance, efficiency, and scalability in advanced manufacturing processes.

Develops physics-inspired deep learning models to advance medical imaging and diagnostic capabilities. Enables extraction of multi-process diagnostic data from single PET scans and performs attenuation correction without additional radiation.
 → Delivering safer, faster, and more cost-effective imaging solutions.

Uses natural language processing and machine learning to analyse electronic health records and detect early signs of deterioration in aged care residents.
 → Recognised by Cooperative Research Australia (Excellence in Innovation Awards, 2024).

Advances trustworthy and equitable recommender systems by addressing bias, transparency, and explainability. Introduces new evaluation approaches that better reflect real-world user behaviour and system robustness.

 Applies deep learning to identify fuel loss sources such as leaks and calibration errors in underground storage systems.
 → Reduces operational costs and environmental impact through more accurate and scalable monitoring solutions.

Translation & Industry Collaboration

RAIsE connects education and research with real-world applications through collaborative industry and enterprise engagement.

The Hub works with industry, government, and community partners to co-design AI initiatives that strengthen capability, inform responsible adoption (aligned with Australia’s Benchmark for Responsible AI Adoption, and translate innovation into practice.

RAIsE acts as a connective platform — bringing together researchers, educators, students, and external partners to explore, prototype, and evaluate AI solutions in context.

Through executive dialogue, co-design workshops, hackathons, and industry-informed curriculum development, RAIsE supports pathways from learning and research into workforce development, policy insight, and applied innovation.

Industry collaborations contribute to curriculum co-development, research dialogue, and capability uplift — with further partnerships continuing to evolve across sectors.

RAIsE operates within and alongside RMIT’s broader AI ecosystem, contributing to enterprise literacy, guardrails, and value realisation conversations while remaining focused on interdisciplinary capability and translation pathways.

AI Thought Leadership

RAIsE convenes leaders across academia, industry, government, and the broader community to explore the strategic, ethical, and organisational implications of artificial intelligence.

Through keynotes, executive forums, panel discussions, industry workshops, and co-designed dialogues, the Hub contributes to national conversations on AI skills, responsible adoption, enterprise readiness, and the future of work. These engagements create shared understanding, strengthen cross-sector collaboration, and support informed decision-making in rapidly evolving AI environments.

Recent activations have included leadership summits, industry governance workshops, academic–industry co-design sessions, hackathons, and public forums focused on AI capability, responsible practice, and workforce transformation.

By bringing together technical expertise, policy insight, and practical experience, RAIsE strengthens RMIT’s role as a trusted contributor to responsible AI discourse and capability development.

To explore opportunities to engage in RAIsE-led discussions and initiatives, please contact the RAIsE Hub at RAIsE@rmit.edu.au.

For updates on events and thought leadership, follow RAIsE on LinkedIn

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Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.

Learn more about our commitment to Indigenous cultures