Computational Mechanics | AI | Materials
From Microstructure to Structural Performance
Developing predictive models for deformation, damage, and failure in advanced engineering systems through computational mechanics, AI-driven engineering, and multiscale materials modelling.
Top 2% Scientist
Stanford/Elsevier
£3M+
Research
Reader
University of Aberdeen
Industry Collaborations
Global Partners
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About Me
I am a Reader in Solid Mechanics & Materials at the University of Aberdeen, working across computational mechanics, advanced materials, manufacturing and structural integrity.
My research connects microstructure, deformation, damage and failure with component and structural performance, combining physics-based modelling, experiments and increasingly AI-enabled computational methods.
Alongside research, I contribute to postgraduate engineering education, PhD supervision, professional activities and industry collaboration, while sharing engineering resources through Professor 3MEC.
Access our most downloaded resources, guides, and modelling tools — free to use.
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Why Do Metals Fail – And Can We Predict It Better?
When a metal component fails, it rarely does so suddenly. Long before a crack becomes visible, damage has already developed at the microscale—through localised deformation,.
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New Research: Metastable Beta Titanium Alloys
Metastable beta titanium alloys are incredibly versatile materials used in aerospace, marine, and biomedical applications due to their unique ability to transform under stress. This.
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Exploring the Complex World of Crystallographic Texture and its Impact on Hydrogen Resistance Properties in Steel
Welcome to my blog where we explore the intriguing world of manufacturing processes and materials science. Today, we delve into the intricate and complex world.
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Predicting the Unpredictable: Machine Learning Tool Forecasts Wind Turbine Blade Erosion
The wind energy industry is growing rapidly as a response to the global call to combat climate change by rapidly decarbonising the energy sector. However,.