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About

Dr. Jingyu Ru is a pioneering researcher at the intersection of underwater robotics, computer vision, and artificial intelligence. Her work primarily focuses on advancing autonomous underwater vehicle (AUV) autonomy through innovative trajectory planning, multi-robot coordination, and visual perception. Her most impactful contribution, "A Bounded Near-Bottom Cruise Trajectory Planning Algorithm for Underwater Vehicles" (25 citations), addresses the critical challenge of navigating complex underwater environments for scientific and industrial missions. She further extends this work with "Research on a hybrid neural network task assignment algorithm for solving multi-constraint heterogeneous autonomous underwater robot swarms" (8 citations), enabling efficient coordination of robot teams for underwater exploration. In the vision domain, Dr. Ru developed RUE-Net (17 citations), a deep learning architecture that significantly advances real-time underwater image enhancement by modeling global and local features—a breakthrough for live visualization in murky waters. Her versatility is demonstrated through STCM-Net (11 citations), a symmetrical one-stage network for temporal language localization in videos, showcasing her expertise in cross-modal AI. With a growing citation impact and a portfolio spanning trajectory optimization, swarm intelligence, and visual enhancement, Dr. Ru is shaping the future of autonomous underwater systems for military, fishery, and energy applications.