Hassan A1, Forsayeth S1, Pineda J1, Tan G1
1Monash University, , Australia
Biography:
Dr. Amr Hassan is Director of Emerging Technologies at Monash University and Program Director of MAVERIC, a AU$60 million AI supercomputing initiative setting a new benchmark for sovereign AI infrastructure in the Australian higher education sector. MAVERIC is delivering next-generation, energy-efficient GPU infrastructure to accelerate large-scale research across health, climate science, life sciences, and drug discovery. His work spans AI-enabled research and enterprise transformation, multi-cloud architecture integrating hyperscale and ISO 27001-certified private cloud, high-density GPU platforms underpinning national AI capability, and cybersecurity governance. Amr's career bridges enterprise IT leadership and research computing, balancing the rigour, scalability, and security of enterprise systems with the agility required to support advanced research and discovery. Over 25 years, he has led teams delivering research computing at national scale, data centre modernisation, enterprise-scale public cloud adoption, and secure enclaves supporting sensitive and regulated workloads.
Abstract:
MAVERIC (Monash AdVanced Environment for Research and Intelligent Computing) is Monash University's sovereign AI supercomputing platform, now in full production as Australia's first Trusted Research Environment (TRE) operating directly on high-performance computing infrastructure, and the country's first deployment of NVIDIA GB200 NVL72 systems.
Australian research increasingly needs to apply large-scale AI methods to sensitive data, from health and the social sciences to nationally significant datasets, under governance that data custodians can rely on. Trusted Research Environments and large-scale AI computing, however, have grown from different traditions. The first is grounded in governance, isolation and auditability, reflected in international practice such as the Five Safes framework. The second is built on scale, openness and shared infrastructure. MAVERIC brings these together, demonstrating that sensitive and ethics-controlled research can be conducted safely on large-scale AI infrastructure.
This presentation reflects on the journey from concept to production. It examines the strategic, architectural and governance choices that shaped the platform, the practical challenges of integrating early-generation AI infrastructure into a university research computing environment, and what it takes to build sovereign AI capability that researchers, data custodians and regulators can trust. It also considers where the path proved harder than expected, and how those experiences are informing the platform's next phase.
As AI reshapes research practice across disciplines, MAVERIC shows that secure research environments and AI supercomputing can converge and provides a working model for delivering research computing that is both powerful and trustworthy.
