Zhenyang Liu

Shenzhen Institute of Information Technology

Papers

Total Citations

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About

Zhenyang Liu is a researcher advancing the intersection of robotics, tactile sensing, and machine learning. His work focuses on enabling machines to perceive and understand physical materials through touch, a critical capability for dexterous manipulation and human-robot interaction. His most-cited paper, "Transformer-based material recognition via short-time contact sensing" (2025), introduces a novel approach that leverages transformer architectures to classify materials from brief tactile interactions. This contribution addresses a key challenge in robotics: how to rapidly and accurately identify surface properties using only limited contact data. By applying attention mechanisms to time-series tactile signals, Liu’s method achieves robust material recognition without requiring extensive exploration or specialized sensors. Though early in its citation trajectory, this work has already garnered 3 citations, signaling growing interest from the tactile sensing and embodied AI communities. Liu’s research holds promise for applications in prosthetics, automated sorting, and smart manufacturing, where real-time material identification is essential. His innovative use of transformers in a non-visual domain marks a notable step toward more intuitive and efficient robotic perception.