Xianbin Zheng
Papers
2
Total Citations
16
H-Index
2
About
Xianbin Zheng is a rising researcher at the intersection of computer vision and intelligent materials, whose work spans both algorithmic efficiency and novel sensor hardware. In deep learning, Zheng is best known for developing reduced-parameter YOLO-like object detectors tailored for resource-constrained platforms—a critical contribution for deploying real-time AI on energy-limited robotics and automotive systems (9 citations). Complementing this computational work, Zheng pioneered fully printed non-contact touch sensors using GCN/PDMS composites, achieving breakthrough capabilities in over-the-bottom detection, 3D spatial recognition, and wireless transmission (7 citations). This dual expertise—optimizing neural networks for edge devices while engineering next-generation electronic skin—positions Zheng as a unique bridge between AI efficiency and tactile sensing. By integrating wearable touch sensors with IoT infrastructure, Zheng’s research lays foundational groundwork for bionic robots that can perceive and interact with their environment more naturally. With both papers published in 2023–2024, Zheng represents an emerging voice in smart sensing and embedded intelligence, demonstrating early impact through innovative, cross-disciplinary solutions.
Research Focus
Key Achievements
Top Papers
- 1
- 2