Jing Ping

Papers

Total Citations

H-Index

About

Jing Ping is a leading researcher in cloud manufacturing and edge computing, whose work addresses critical challenges in Industry 4.0 smart factories. Her primary research areas include hybrid scheduling models, task decomposition, and resource allocation for edge industrial services. In her highly cited 2020 paper, "A cloud edge-based two-level hybrid scheduling learning model in cloud manufacturing" (49 citations), she pioneered a two-level scheduling framework that significantly reduces scheduling time and communication delays while balancing loads among edge nodes. This contribution directly tackles the inefficiencies of smart robotic services and distributed manufacturing systems, offering a scalable solution for real-time decision-making. Her work has been instrumental in advancing the integration of cloud and edge computing for industrial automation, earning recognition for its practical impact on reducing latency and improving system reliability. Jing Ping’s research continues to influence the design of intelligent manufacturing workflows, making her a key figure in the evolution of smart factory technologies.