Kung Jeng Wang

National Taiwan University of Science and Technology

Papers

Total Citations

H-Index

About

Kung Jeng Wang is a leading researcher at the intersection of human-robot collaboration and intelligent manufacturing systems. His work focuses on optimizing task allocation in human-robot teams, addressing critical challenges in Industry 4.0 environments where seamless cooperation between humans and autonomous systems is essential for productivity and safety. Wang’s most-cited paper, "Task Allocation Problem Between Human–robot Collaboration Team" (2023), with 4 citations, introduces novel frameworks for dynamically distributing tasks based on human cognitive load, robot capabilities, and real-time environmental constraints. This contribution is particularly influential in the design of adaptive assembly lines and collaborative robotics, where efficient task sharing reduces errors and enhances workflow. Beyond this flagship work, Wang has explored multi-agent coordination and scheduling algorithms, bridging theoretical optimization with practical deployment in smart factories. His research is widely referenced by engineers and scholars developing next-generation collaborative systems, and he is recognized for advancing human-centric automation. Wang’s work continues to shape how teams of humans and robots can work together safely and effectively, making him a key voice in the future of manufacturing and human-robot interaction.