The presenter
Dr Bill Murari
Research Fellow Industrial AI Research Centre
University of South Australia
Dr Bill Murari specialises in applying machine learning to solve complex problems in aerospace and mechanical engineering. His research focuses on using AI-driven modelling and optimisation techniques to predict the behaviour of advanced composite materials, supporting the development of more sustainable and efficient engineering solutions. With a background in aerospace engineering and a PhD in mechanical engineering, Dr Murari brings together expertise in structural analysis, computational modelling, and AI applications. He has worked across academia and industry, developing innovative tools and simulations that streamline processes and improve design outcomes. At the core of his work is a commitment to bridging engineering fundamentals with intelligent automation—empowering innovation through data-driven, machine learning approaches.
Dr Bill Murari, University of South Australia, will present a seminar on
Thursday, 3rd July 2025.
Title: What if AI could help us discover next-generation materials not in decades, but in months?
Abstract: With the rapid rise of machine learning and artificial intelligence, my recent research explores their transformative impact on materials discovery and development. In fields like aerospace and defence, there is a growing and urgent demand for materials that are both lightweight and high-strength — a combination rarely found in nature and historically costly to develop through traditional experimentation.
This work leverages ML techniques to accelerate the identification and evaluation of novel materials, reducing the time, cost, and uncertainty typically involved in R&D. By learning from existing datasets and extrapolating to new chemical or structural domains, ML models can prioritise the most promising material candidates — making experimental campaigns more focused and resource-efficient.
For defence applications, where material performance is critical and operational timelines are tight, this approach offers a strategic advantage: the ability to move faster from concept to deployment, with lower risk and higher confidence. This talk will provide an overview of the methodology, early results, and its potential to shift how we approach material innovation in high-stakes engineering environments.
Click the button below to register, add an invitation to your calendar and join the seminar using the Teams/GovTeams link.
