Dr Bill Murari

Research Fellow

School of Electrical and Mechanical Engineering

College of Engineering and Information Technology

Available For Media Comment.


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 materials engineering, computational mechanics and machine learning assisted modelling. 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.

Date Institution name Country Title
2024 RMIT University Australia PhD
2020 RMIT University Australia Bachelor's Degree (Honours)

Year Citation
2026 Murari, B., Wegert, Z. J., Wilks, B., Ghayesh, M. H., Thamwattana, N., Challis, V. J., & Meylan, M. H. (2026). Wave energy conversion using submerged piezoelectric plates with functionally graded graphene origami-enabled auxetic metamaterial substrates: A hydroelectromechanical study. Ocean Engineering, 363(P2), 11 pages.
DOI
2024 Murari, B., Zhao, S., Zhang, Y., & Yang, J. (2024). Machine learning-assisted vibration analysis of graphene-origami metamaterial beams immersed in viscous fluids. Thin-Walled Structures, 197(111663), 1-15.
DOI Scopus43 WoS42
2024 Murari, B., Zhao, S., Zhang, Y., & Yang, J. (2024). Vortex-induced vibration of a functionally graded metamaterial plate attached to a cylinder in laminar flow. Thin-Walled Structures, 199(111790), 1-10.
DOI Scopus20 WoS20
2023 Murari, B., Zhao, S., Zhang, Y., & Yang, J. (2023). Static and dynamic instability of functionally graded graphene origami-enabled auxetic metamaterial beams with variable thickness in fluid. Ocean Engineering, 280(114859), 1-12.
DOI Scopus67 WoS66
2023 Murari, B., Zhao, S., Zhang, Y., Ke, L., & Yang, J. (2023). Vibrational characteristics of functionally graded graphene origami-enabled auxetic metamaterial beams with variable thickness in fluid. Engineering Structures, 277(115440), 1-17.
DOI Scopus79 WoS81
2023 Murari, B., Zhao, S., Zhang, Y., & Yang, J. (2023). Graphene origami-enabled auxetic metamaterial tapered beams in fluid: Nonlinear vibration and postbuckling analyses via physics-embedded machine learning model. Applied Mathematical Modelling, 122, 598-613.
DOI Scopus65 WoS65

Connect With Me

External Profiles

Other Links