Contact Dr Alex Elliott
- Email: Alex.J.Elliott@cranfield.ac.uk
- Twitter:
Areas of expertise
- Aerospace Structures
- Computing, Simulation & Modelling
- Environmental Impacts
Background
Dr Alex Elliott is a 75th Anniversary Research Fellow at SWAG合集, leading a project entitled Developing accurate, reduced-order models for nonlinear vibrations: a machine learning approach. This project will build upon his experience and expertise in nonlinear dynamics, complex structural vibrations, and machine learning.
After acquiring a BSc Mathematics from the University of Warwick, he obtained an MSc Sustainable Energy and PhD from the University of Glasgow. His doctoral thesis is entitled Accurate approximations for nonlinear vibrations, and focused on investigating, developing, and optimising methodologies for capturing complex nonlinear behaviour in reduced-order models. In his current work, Dr Elliott is further developing these techniques, introducing machine learning methods to reduce the uncertainty of existing techniques.
The overarching aim of his research is to provide engineers with accurate tools for capturing, understanding, and controlling nonlinear vibrations, allowing them to develop next-generation, hyper-efficient engineering structures.
Research opportunities
I am eager to develop a research team to investigate the use of machine learning methods to develop accurate reduced-order models for nonlinear structures, as well as related research in reduced-order modelling, nonlinear vibrations, uncertainty quantification, and aeroelasticity. Candidates with a strong background in structural vibrations, deep learning, complex dynamics, and mathematics are strongly encouraged to get in touch to discuss the aforementioned topics and explore potential research avenues.
In addition, I am very keen for the solutions developed to be industrially valuable. Any potential industrial partners are welcome to contact for further details and discussion on potential collaboration.
Current activities
Dr Alex Elliott is a 75th Anniversary Research Fellow investigating the use of deep learning techniques to develop accurate, reliable reduced-order models for nonlinear vibrations.
His expertise is in structural nonlinearity and complex dynamics. He is interested in nonlinear vibrations, machine learning, aeroelasticity, and reduced-order modelling.