Liang Yin
Papers
1
Total Citations
6
H-Index
1
About
Liang Yin is a researcher at the intersection of brain-computer interfaces (BCIs) and intelligent control systems, with a focus on enhancing human-machine collaboration. His most-cited work, "Design and Implementation of Petri Net for Brain-Computer Interface System" (2019, 6 citations), introduces a novel shared control method that integrates human and machine intelligence through Petri net modeling. By partitioning BCI systems into functional modules and incorporating control places into ordinary Petri nets, Yin’s approach enables more precise and adaptive coordination between neural signals and automated responses. This contribution addresses a critical challenge in BCI design—balancing user intent with system autonomy—and has implications for assistive technologies, neuroprosthetics, and interactive robotics. While his citation count reflects an emerging career, the conceptual rigor of his Petri net framework offers a foundational tool for future BCI system development. Yin’s work exemplifies how formal modeling methods can bridge cognitive neuroscience and engineering, paving the way for more intuitive and reliable brain-driven interfaces.
Research Focus
Key Achievements
Top Papers
- 1