Shijing Hu
Papers
2
Total Citations
5
H-Index
2
About
Shijing Hu is at the forefront of embodied intelligence (EI) and edge-cloud computing for smart manufacturing. Their research centers on integrating large vision models with adaptive edge-cloud collaboration to enable flexible, real-time perception and reasoning in dynamic industrial environments. Hu’s most cited work, "LAECIPS: Large Vision Model Assisted Adaptive Edge–Cloud Collaboration for IoT-based Embodied Intelligence System," demonstrates how robotic visual inspection can be revolutionized by offloading complex vision tasks between edge devices and cloud servers. This approach allows industrial robots to accurately inspect components on fast-moving production lines, overcoming latency and computational constraints. With over 5 combined citations for this emerging work, Hu’s contributions are gaining traction in the IoT and manufacturing communities. Their research directly addresses the critical challenge of deploying embodied intelligence in real-world shop floors, where adaptability and speed are paramount. Hu’s work is particularly notable for bridging large-scale AI models with resource-constrained edge systems, paving the way for more autonomous and responsive manufacturing ecosystems.
Research Focus
Key Achievements
Top Papers
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- 2