Lulu Chen
Papers
2
Total Citations
31
H-Index
2
About
Lulu Chen is a rising researcher at the intersection of industrial AI, fog computing, and autonomous systems. Her work addresses critical challenges in smart manufacturing, particularly the management of heterogeneous workloads in fog-based environments. In her highly cited 2022 paper, “A Resource Recommendation Model for Heterogeneous Workloads in Fog-Based Smart Factory Environment” (26 citations), Chen proposed a novel framework for efficiently processing the massive, varied data streams generated by IIoT-enabled robots—a key contribution to maintaining productivity and safety in Industry 4.0 settings. More recently, Chen has turned her attention to the frontier of autonomous AI agents. Her 2025 paper, “From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent” (5 citations), provides an early analysis of Manus AI, a general-purpose agent developed by Monica.im that bridges reasoning and execution. This work positions Chen as a forward-looking commentator on the evolution of AI from tools to autonomous actors. With a growing citation footprint and a focus on both practical industrial optimization and cutting-edge AI paradigms, Lulu Chen is a researcher to watch in the rapidly converging fields of edge intelligence and autonomous systems.
Research Focus
Key Achievements
Top Papers
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