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parametric reduced order models of operating wind turbines, information contained in their differential geometry and safe data-driven control/reinforcement learning tools jointly developed with the second PhD
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how geometry- and data-driven digital twins of wireless environments can support learning, inference, and coordination in physical AI systems such as robots, vehicles, or distributed sensing platforms
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