Papers
3
Total Citations
37
H-Index
2
About
Yumeng Lei is a pioneering researcher at the intersection of artificial intelligence, mechanical systems prognostics, and telemedicine. Her work is defined by two distinct but equally impactful streams: developing advanced deep learning models for industrial predictive maintenance, and evaluating next-generation 5G-enabled robotic teleultrasound systems for healthcare accessibility. Lei’s most influential contribution is the introduction of VSC-Net, a versatile spatiotemporal convolution network that fuses multi-sensor signals to predict the remaining useful life of mechanical systems—a critical advancement for industrial reliability. This work has already garnered 23 citations since its 2025 publication, signaling rapid adoption in the prognostics and health management community. In the healthcare domain, Lei led a landmark feasibility study on 5G-based robotic teleultrasound for routine health check-ups in underserved rural areas, demonstrating both technical viability and high participant satisfaction (12 citations). She further advanced this field by developing a structural equation model to systematically analyze the multi-dimensional factors influencing user satisfaction with remote ultrasound robots. Through these contributions, Lei is bridging cutting-edge AI with real-world challenges in industrial sustainability and equitable healthcare delivery.
Research Focus
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Top Papers
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