Chao Tong

Beihang University, Jiangxi Science and Technology Normal University

Papers

Total Citations

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About

Chao Tong is a researcher at the forefront of intelligent robotics and embedded artificial intelligence, with a focus on deploying efficient, real-world AI systems. His work bridges the gap between advanced computer vision algorithms and practical robotic applications, particularly in autonomous navigation and multi-modal sensor fusion. Tong’s 2023 paper on designing a multi-modal sensor fusion unmanned vehicle system, which integrates computer vision with other sensory inputs, has garnered significant attention, earning 3 citations for its contributions to robust, real-time robotic perception. More recently, his 2025 study, “SlimDL: Deploying ultra-light deep learning model on sweeping robots,” addresses a critical challenge in consumer robotics: enabling powerful deep learning models to run on resource-constrained hardware. This work, also with 3 citations, demonstrates his ability to optimize AI for low-power, cost-sensitive devices like sweeping robots and library service robots. Tong’s research is not only technically rigorous but also highly applicable, directly impacting the efficiency and intelligence of everyday autonomous systems. His achievements highlight a dedication to making AI accessible and functional in practical, real-world environments.