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About

Ruyu Luo is an emerging researcher at the intersection of wireless communications, robotics, and artificial intelligence, with a particular focus on intelligent resource management for multi-robot systems in next-generation networks. His work addresses fundamental challenges in the Internet of Robotic Things (IoRT), where robot mobility, dynamic wireless environments, and complex communication demands must be simultaneously managed. Luo has made significant contributions by applying deep reinforcement learning and federated learning frameworks to jointly optimize robot trajectories and communication resources — problems that are notoriously difficult due to their coupled, high-dimensional nature. A hallmark of his research is the integration of reconfigurable intelligent surfaces (RIS) to combat signal blockages in indoor environments, a contribution that has attracted 34 citations and influenced subsequent RIS-robotics literature. His multi-agent reinforcement learning approaches for industrial IoT settings further demonstrate his commitment to scalable, practical solutions for smart factory applications. Collectively, his publications have garnered nearly 80 citations, reflecting growing recognition from the research community. With his most recent work in 2025 continuing to advance RIS-assisted multi-robot systems, Luo represents a promising voice in the rapidly evolving field of intelligent connected robotics.