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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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aerospace, healthcare, and industrial automation. In safety-critical domains, such as aviation and medical devices, rigorous certification processes and continuous lifecycle monitoring are essential to ensure
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
) to engineers and automated systems •Validate the system’s resilience, scalability, and practical relevance using real-world and representative datasets, with evaluation of technical performance and potential
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significant relevance in today's technological landscape. As industries continue to integrate digital and physical systems, the role of eCPS in enhancing automation, control, and sustainability becomes