Haibin Yu

Papers

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About

Haibin Yu is an emerging researcher working at the intersection of robotics, wireless communications, and artificial intelligence. His work focuses on the integration of control systems and communication networks for cloud-connected robotic platforms, an increasingly critical area as autonomous systems become more reliant on distributed computing infrastructure. His most notable contribution, "Control-Communication Co-Optimization for Wireless Cloud Robotic System via Multi-Agent Transfer Reinforcement Learning," demonstrates a sophisticated approach to jointly optimizing control and communication resources in wireless cloud robotic systems using multi-agent transfer reinforcement learning — a technique that enables knowledge sharing across agents to improve efficiency and adaptability in dynamic environments. Published in 2026 and already accumulating citations, this work addresses a fundamental challenge in networked robotics: how to balance the demands of real-time control with the constraints of wireless communication bandwidth and latency. While Yu's citation profile is still developing, reflecting an early-career trajectory, his research sits at a timely and high-impact frontier, with broad implications for autonomous vehicles, industrial automation, and next-generation networked robotic systems. Researchers in AI-driven robotics and wireless networks would find his work particularly relevant.