Mengyi He

Papers

Total Citations

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About

Mengyi He is a leading researcher in intelligent acoustic sensing and human-machine interaction, with a focus on triboelectric nanogenerators and deep learning. Their most cited work introduces a deep learning-enhanced anti-noise triboelectric acoustic sensor designed for robust voice interaction in noisy environments—a critical advancement for applications in health monitoring, post-disaster rescue, and intelligent control. By integrating flexible sensor design with neural network-based noise suppression, He’s system overcomes the limitations of conventional microphones, achieving reliable speech recognition under challenging acoustic conditions. This paper has already garnered 24 citations since its 2025 publication, reflecting its immediate impact on the field. He’s contributions bridge materials science, signal processing, and artificial intelligence, offering a practical pathway toward seamless human-machine collaboration in real-world settings. Their work stands out for addressing a persistent bottleneck in voice-controlled systems—ambient noise interference—and for demonstrating a scalable, energy-efficient solution. As a rising scholar, Mengyi He is shaping the next generation of smart acoustic interfaces, with potential to transform how humans interact with machines in both everyday and emergency contexts.