Papers
1
Total Citations
4
H-Index
1
About
Xiaofeng Ma is a researcher at the forefront of human-robot collaboration, with a specific focus on trust dynamics and automation in remote construction tasks. His most-cited work, "Human trust effect in remote human–robot collaboration construction task for different level of automation" (2025), has garnered 4 citations, establishing a foundation for understanding how varying levels of automation influence operator trust and performance in high-stakes environments. Ma’s key contributions lie in quantifying the nuanced interplay between human cognitive factors and robotic system design, offering empirical evidence that trust is not static but modulated by automation transparency and task complexity. This work has direct implications for improving safety and efficiency in construction, where remote collaboration is increasingly vital. By bridging human factors engineering and robotics, Ma provides actionable insights for developing adaptive automation strategies that maintain operator confidence without over-reliance. His research is particularly notable for its practical application to real-world construction scenarios, making him a rising voice in the field of human-robot interaction. As automation continues to reshape industries, Ma’s findings serve as a critical guide for designing systems that earn and sustain human trust.
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Top Papers
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