Papers
2
Total Citations
315
H-Index
2
About
Mei Li is a leading researcher at the intersection of human-machine interaction and intelligent industrial systems. Her work spans two critical domains: the psychological measurement of attitudes toward artificial intelligence and the application of deep learning for predictive maintenance in manufacturing. Li’s landmark 2020 paper, "Assessing the Attitude Towards Artificial Intelligence," introduced a validated short-form scale in German, Chinese, and English, accumulating over 305 citations and becoming a foundational tool for cross-cultural studies on AI acceptance. This work has been instrumental in understanding how skepticism and enthusiasm shape technology adoption. More recently, Li has pioneered fault prediction methods for rolling element bearings in industrial robots, combining digital twin technology with deep transfer learning to overcome the limitations of traditional diagnosis that require extensive historical data. Her 2025 paper on this topic demonstrates a practical solution to reduce system downtime and repair costs in manufacturing. Li’s dual focus on human factors and engineering reliability positions her as a unique bridge between social science and industrial AI, with her citation record reflecting the broad impact of her contributions across disciplines.
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