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will have the opportunity to investigate innovative solutions using machine learning algorithms and predictive modelling techniques in the context of a collaborative project with Goodyear Luxembourg (one
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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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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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twins together with two PhD students, especially to propose new models and algorithms for complex maneuvers, and building a parametric autonomous model of drivers reproducing a close to reality human
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Testing and Experimentation Facility (TEF) for the energy field. Specifically, it leverages AI and cutting-edge infrastructure to optimize EV charging and energy systems. By integrating distributed energy