Suhang Liu

Sun Yat-sen University

Papers

1

Total Citations

24

H-Index

1

About

Suhang Liu is a rising leader in intelligent sensing and human-machine interaction, with a research focus on triboelectric nanogenerators, acoustic sensors, and deep learning-enhanced signal processing. His most-cited work introduces a deep learning-enhanced anti-noise triboelectric acoustic sensor designed for robust human-machine collaboration in noisy environments. This innovation directly addresses the critical challenge of voice interaction reliability under real-world acoustic interference, achieving 24 citations since its 2025 publication. Liu’s contributions bridge the gap between self-powered sensor technology and advanced neural network architectures, enabling intuitive, efficient voice control for applications ranging from health monitoring to post-disaster rescue and intelligent automation. By integrating noise-resistant algorithms with flexible triboelectric materials, his research pushes the boundaries of speech recognition in harsh acoustic settings. Liu’s work stands out for its practical impact, offering a scalable pathway toward more resilient and user-friendly human-machine interfaces. As an emerging voice in the field, his achievements signal a promising trajectory for next-generation acoustic sensing and intelligent systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
24
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Deep learning-enhanced anti-noise triboelectric acoustic sensor for human-machine collaboration in noisy environments
24 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Sun Yat-sen University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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