Jianglong Yang
Papers
2
Total Citations
39
H-Index
2
About
Dr. Jianglong Yang is a leading researcher in intelligent logistics and robotic automation, with a focus on transforming supply-chain operations through deep learning and optimization. His most cited work, "Deep-Learning-Based Accurate Identification of Warehouse Goods for Robot Picking Operations" (2022, 31 citations), pioneers the use of convolutional neural networks to enable precise, real-time object recognition for autonomous sorting, directly addressing the industry’s need for energy-efficient and unmanned warehousing. Building on this, his recent study "Warehouse layout optimization for fishbone robotic mobile fulfillment systems" (2024, 8 citations) introduces novel geometric configurations that significantly reduce travel time and congestion in robotic fulfillment centers. These contributions have established Dr. Yang as a key figure in digital logistics, bridging theoretical optimization with practical deployment. His research not only advances the efficiency of robot picking and layout design but also supports broader sustainability goals in supply-chain management. With a growing citation impact, Dr. Yang’s work is essential reading for engineers and researchers seeking to integrate AI and robotics into next-generation warehousing systems.
Research Focus
Key Achievements
Top Papers
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- 2