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My expertise lies in aerospace and mechanical engineering & machine learning assisted modelling.
With the advent of AI and machine learning, my research has focused on implementing machine learning techniques to predict the mechanical behaviours of novel composite structures. While this area of research is in its nascent stage, there is clear evidence that the robustness of machine learning allows engineers, scientists and researchers to explore the vast world of composite structures while conserving resources. Developing advanced materials remains the single most effective solution to a cleaner, greener and energy efficient future. With the help of machine learning techniques, the future we hope for is within reach.
Services
Services
Discover how I can support you and your work.
Software & Simulation
Software & Simulation
I develop custom AI-powered software solutions to automate engineering workflows, optimise designs, and streamline compliance processes. My expertise in Python, MATLAB, JavaScript, and CAD modelling allows us to create innovative tools that reduce manual effort, improve accuracy, and enhance decision-making. Whether it's aerospace design automation, structural analysis software, or simulation-driven product development, I deliver tailored solutions that maximise efficiency and performance.
Aerospace Structural Analysis
Aerospace Structural Analysis
I specialise in the design, simulation, and optimisation of high-performance aerospace structures using cutting-edge composite materials. My expertise in finite element analysis (FEA), fluid-structure interactions, and AI-driven modelling enables us to develop lightweight, durable, and efficient solutions for the aviation and space industries. From carbon fibre composites to graphene-based metamaterials, I enhance structural integrity while optimising weight and performance.
Computational Mechanics
Computational Mechanics
Harnessing the power of computational mechanics, machine learning, and genetic algorithms, I develop predictive models that revolutionise engineering design and analysis. My expertise includes nonlinear vibrations, post-buckling behaviour, and vortex-induced vibrations for aerospace and mechanical structures. By integrating physics-based simulations with AI, I provide faster, more accurate insights into complex engineering challenges.
My Research
My Research
Machine learning-assisted vibration analysis of graphene-origami metamaterial beams immersed in viscous fluids
Machine learning-assisted vibration analysis of graphene-origami metamaterial beams immersed in viscous fluids
My research explores the dynamic behavior of functionally graded graphene origami-enabled auxetic metamaterial (FG-GOEAM) beams submerged in Newtonian fluids, with a particular focus on the impact of negative Poisson’s ratio (NPR) on their vibrational characteristics. To enhance accuracy and computational efficiency, I developed an advanced machine learning-assisted model based on genetic programming (GP), integrated with theoretical formulations.
Using first-order shear deformation theory and solving with the differential quadrature method (DQM) and Newmark–β method, my study incorporates fluid-structure interaction (FSI) principles derived from the Navier–Stokes equation. Results highlight the exceptional predictive capability of the machine learning framework, demonstrating that graphene origami (GOri) reinforcements significantly enhance NPR properties. Compared to traditional metallic beams, FG-GOEAM structures exhibit superior frequency response and enhanced resistance to dynamic deflections. This research advances the understanding of metamaterial composites and underscores the potential of AI-driven optimization in structural analysis.
Vortex-induced vibration of a functionally graded metamaterial plate attached to a cylinder in laminar flow
Vortex-induced vibration of a functionally graded metamaterial plate attached to a cylinder in laminar flow
Fluid-structure interaction (FSI) plays a crucial role in engineering applications, particularly in vortex-induced vibration (VIV) studies. My research provides a comprehensive numerical investigation into the VIV behavior of functionally graded (FG) graphene origami-enabled auxetic metamaterial (GOEAM) splitter plates attached to a circular cylinder. Using finite element analysis and Yeoh smoothing to enhance mesh quality, this study examines the influence of auxetic properties on vibration responses, wake patterns, and fluid loads.
Key findings reveal that GOEAM structures with high-gradient reinforcement exhibit lower deflection amplitudes, while plate length significantly affects vortex formation—shorter plates intensify vortices, whereas longer plates suppress them. Additionally, both FG-GOEAM and metallic plates maintain natural frequencies well above vortex shedding frequencies, ensuring minimal impact from fluid loads. These insights advance our understanding of fluid-structure interactions and contribute to the optimization of graphene-based metamaterial structures for real-world engineering applications.
My Story
My Story
From an early age, I was captivated by the intricate mechanics of how things work—whether it was the aerodynamics of an aircraft or the computational models behind structural analysis. This passion led me to pursue a career in aerospace and mechanical engineering, blending my expertise in composite materials, computational modelling, and AI-driven simulations to push the boundaries of innovation.
My journey began with an Aerospace Engineering degree at RMIT University, where I honed my skills in aerodynamics, structural analysis, and advanced materials. A deep interest in computational mechanics and AI applications in engineering propelled me toward a PhD in Mechanical, Manufacturing and Mechatronics Engineering, where I explored fluid-structure interactions of graphene-based composites—work that contributed to cutting-edge advancements in the field.
Alongside my research, I gained hands-on industry experience, including developing an innovative software tool for an aircraft certification company, significantly reducing compliance processes. My roles as a researcher, lecturer, and design engineer allowed me to merge academia, industry, and innovation, providing real-world solutions through machine learning, CAD design and advanced simulations.
Today, I apply my expertise through my engineering consultancy, offering technical analysis, design solutions, and research insights to industry leaders. My goal is to bridge the gap between engineering fundamentals and AI-driven automation, helping organisations optimise their processes, enhance efficiency, and stay ahead in an evolving technological landscape.
This journey is driven by one core belief: engineering is more than problem-solving—it’s about redefining possibilities.
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