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About

Dr. Yaqing Hou is a leading researcher at the intersection of multirobot systems, evolutionary optimization, and human-robot interaction. Her work fundamentally addresses how autonomous agents—from air combat robots to robotic arms—can learn, adapt, and coordinate in complex, dynamic environments. Dr. Hou’s major contributions include pioneering a spatiotemporal relationship cognitive learning framework for multirobot air combat, enabling autonomous systems to understand and react to time-varying adversarial relationships. She has also advanced 3D human motion prediction with a deformable transformer-based adversarial network, tackling the critical challenge of generating plausible, efficient motion for seamless human-robot collaboration. In evolutionary robotics, Dr. Hou has introduced innovative knowledge transfer mechanisms, such as multi-task MAP-Elites and genetic algorithms, to optimize both the design and control of robotic arms across diverse industrial tasks. Her work on safety-guided deep reinforcement learning further ensures that autonomous mobile robots can navigate open, unpredictable environments without compromising safety. With her most cited paper (2023) garnering 12 citations and a growing portfolio of work from 2021 to 2025, Dr. Hou is shaping the future of intelligent, safe, and adaptive multi-agent systems.