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collaborations with industry giants including Boeing, Rolls-Royce, Thales, and UKRI, this research offers a unique platform to contribute to the advancement of intelligent assurance methodologies in sectors like
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. By integrating artificial intelligence (AI), multi-sensor fusion, and cognitive systems, the research will pioneer robust navigation architectures. These improvements are key to making future transport
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM
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at the internationally recognised IVHM Centre, the research is supported by collaborations with Boeing, Rolls-Royce, Thales, and UKRI, offering a unique environment for cutting-edge work in fault-tolerant hardware
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research projects across areas such as: Zero Emission Technologies. Ultra Efficient Aircraft, Propulsion, Aerodynamics, Structures and Systems. Aerospace Materials, Manufacturing, and Life Cycle Analysis
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more research is required to establish the inter-dependencies between these properties with the help of high resolution images. In this research, different sets of composites material will be dynamically
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attracted intense interest from both academia and industry recently for its attempt to extract more useful information and knowledge from Big Data. Big Data analytics will help to develop more advance