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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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use by the group employ multiple-input multiple-output (MIMO) technology and can be connected to build a distributed and cooperative network. To develop signal processing techniques, the group
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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), sensing technologies (fiber-optic sensors, DIC), and computer science (machine learning tools). The aim of this Ph.D. project is to develop a novel bridge monitoring technique based on CLCE coating