Zhengjie Liu

Papers

Total Citations

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About

Zhengjie Liu is a pioneering researcher at the forefront of human-machine interaction and intelligent sensing technologies. His work centers on developing advanced acoustic sensors and deep learning frameworks that enable seamless voice-based collaboration between humans and machines, even in the most challenging environments. Liu’s major contribution is the creation of a deep learning-enhanced anti-noise triboelectric acoustic sensor, which overcomes the limitations of conventional microphones by maintaining high speech recognition accuracy in noisy settings. This innovation has direct applications in health monitoring, post-disaster rescue operations, and intelligent control systems. His most-cited paper, published in 2025, has already garnered 24 citations, reflecting the rapid impact and relevance of his work. By integrating triboelectric nanogenerators with sophisticated noise-filtering algorithms, Liu has opened new pathways for robust, real-time voice interaction in real-world conditions. His research not only advances the field of human-machine collaboration but also promises to improve safety and efficiency in critical scenarios, making him a notable emerging voice in next-generation sensing and AI-driven interface design.