Chunfeng Wei
Papers
2
Total Citations
36
H-Index
2
About
Chunfeng Wei is a researcher at the intersection of robotics, brain-computer interfaces, and industrial automation. His work focuses on developing intelligent systems that bridge human intention and machine action, with particular emphasis on EEG-based control and deep learning for robotic manipulation. Wei’s most cited contribution, “Online interaction method of mobile robot based on single-channel EEG signal and end-to-end CNN with residual block model” (2022, 31 citations), pioneers a streamlined approach to non-invasive neural control, enabling real-time robot navigation through minimal EEG data. This work demonstrates how compact convolutional neural networks can decode cognitive commands with remarkable efficiency. In parallel, his research on “An industrial intelligent grasping system based on convolutional neural network” (2022, 5 citations) addresses a critical bottleneck in manufacturing: the time-intensive process of dataset creation. By designing a CNN-based system that achieves high gripping success rates while reducing deployment complexity, Wei advances practical, cost-effective automation for real-world industrial settings. His contributions exemplify how deep learning can make robotic systems both more intuitive for human operators and more adaptable for factory floors, positioning him as a rising voice in applied intelligent robotics.
Research Focus
Key Achievements
Top Papers
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