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. Focusing on adaptive intelligence, which blends human creativity and machine intelligence, the project will develop Multi-Intelligence Agents (MIAs) to facilitate the seamless integration of social factors
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-disciplinary approach that integrates design, technology and management expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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response have led to targets for reducing overflow frequency, ecological harm, visual impacts, and protecting bathing water. This PhD project has been co-developed with four UK water companies and the
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the operational life of battery-powered devices and reducing the environmental impact of large-scale deployments. Advancements in this area support the development of sustainable technologies across various
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the development of specialized hardware architectures capable of efficient, real-time processing. Embedded AI hardware architectures, including neuromorphic processors and low-power AI accelerators
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vulnerabilities like side-channel attacks and unauthorized access, which can compromise system integrity. Developing robust security measures within AI-enabled electronics is essential for applications in defence
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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
. This PhD project will tackle that challenge by developing intelligent methods that combine AI techniques such as language models that interpret technical text and knowledge graphs that map engineering