Mingyu Jin
Papers
1
Total Citations
3
H-Index
1
About
Mingyu Jin is a researcher at the forefront of intelligent manufacturing and human-robot interaction, with a particular focus on enhancing workplace safety through advanced computational methods. His most cited work, "Emergency Stop System of Computer Vision Workstation Based on GMM-HMM and LSTM" (2023, 3 citations), pioneers the integration of voice recognition and command technology with industrial robotics. This research addresses a critical gap in manufacturing: enabling operators with minimal specialized training to safely and intuitively control robotic systems. By combining Gaussian Mixture Models, Hidden Markov Models, and Long Short-Term Memory networks, Jin developed a robust emergency stop mechanism that responds to voice commands, significantly reducing the skill barrier for robot manipulation. His contributions are particularly notable for bridging the gap between complex machine learning architectures and practical industrial safety applications. While still early in his career, Jin's work demonstrates a clear trajectory toward making intelligent manufacturing more accessible and safer. His research holds promise for transforming how humans interact with industrial robots, potentially reshaping safety protocols across the manufacturing sector.
Research Focus
Key Achievements
Top Papers
- 1