Papers
7
Total Citations
103
H-Index
5
About
Keping Yu is a multidisciplinary researcher whose work spans robotics, artificial intelligence, and advanced manufacturing, with a particular focus on developing intelligent systems that bridge human-machine interaction and autonomous decision-making. Yu's most impactful contribution to date is a deep reinforcement learning-based approach for autonomous robotic path planning in blind areas, which has garnered an impressive 65 citations since its publication in 2024, signaling its rapid adoption within the robotics and AI community. His research into knowledge graph-based question answering for human-robot interaction demonstrates a commitment to making robotic systems more conversationally capable and cognitively aware, employing question-aware memory networks to handle complex, multi-hop reasoning tasks. Beyond software and AI, Yu has extended his research into physical robotics hardware, publishing innovative work on multi-material additive manufacturing and heated syringe extrusion techniques for fabricating pneumatically driven soft grippers. His editorial contributions to computational social systems further reflect his broad intellectual range and engagement with emerging AI-driven societal frameworks. Yu represents a new generation of researchers who seamlessly integrate intelligent algorithms with tangible robotic engineering, making meaningful strides across both theoretical and applied domains.
Research Focus
Key Achievements
Top Papers
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- 3Artificial Intelligence8 citations · 2021
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