We use computational methods to study phenomena governed by the principles of solid and fluid mechanics and develop numerical methods to tackle complex engineering problems that cannot be solved via commercially available software. Our expertise lies in the Development of Computational Methods, Structures, Geotechnics, Optimisation of Power Grids and Circuits, Computational Fluid Dynamics, Predicting Material Properties and Application of Artificial Intelligence

We aim to 

• work at the forefront of development of computational methods for solid mechanics
• develop new applications for our computational methods across the engineering disciplines and beyond

Areas of interest:

• Development of computational methods, and their application to structures, geotechnics, waves & fluid flow
• Development of optimisation techniques with applications in power grids and circuits and other inverse problems
• Application of Artificial Intelligence, Uncertainty Quantification and Machine Learning to engineering problems

Node leader:

• Mohammed Seaid

Academic Core members:

• Charles Augarde
• Will Coombs
• Stefano Giani
• Bartolomeo Panto'
• Stefan Szyniszewski
• Jon Trevelyan
• Martin Walker
• Qing Wang