Jiaqi Liang
Papers
3
Total Citations
70
H-Index
2
About
Jiaqi Liang is an emerging researcher specializing in smart warehouse optimization, human-robot collaboration, and intelligent logistics systems. Their work sits at the intersection of robotics, the Internet of Things, and operations research, with a particular focus on robotic mobile fulfillment systems (RMFSs) that are rapidly transforming modern e-commerce and supply chain operations. Liang's most influential contribution, "Order Picking Optimization in Smart Warehouses With Human–Robot Collaboration" (2024), has already garnered an impressive 65 citations, reflecting the timeliness and significance of their research in addressing the complex coordination challenges that arise when robots and human pickers work together in goods-to-person systems. Their work tackles intricate sub-problems including pod selection, multi-robot task allocation, and station scheduling — challenges that have real-world implications for warehouse efficiency and labor productivity. Building on this foundation, Liang has pioneered learning-based approaches to integrate multiple operational optimization problems simultaneously, moving beyond traditional methods to embrace machine learning as a tool for solving dynamic, large-scale logistics challenges. Though early in their career, Liang's rapidly growing citation record and consistent focus on human-robot collaborative systems position them as a promising voice in intelligent manufacturing and autonomous logistics research.
Research Focus
Key Achievements
Top Papers
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