Zhengshan Cui
Papers
1
Total Citations
18
H-Index
1
About
Zhengshan Cui is a researcher at the forefront of robotic manipulation and tactile sensing, with a focus on integrating deep learning with physical interaction. His most-cited work, "Deep learning with tactile sequences enables fruit recognition and force prediction for damage-free grasping" (2023, 18 citations), exemplifies his key contribution: developing intelligent systems that allow robots to handle delicate objects—like fruit—without causing damage. By combining tactile sequence data with neural networks, Cui’s research enables machines to both recognize objects by touch and predict the precise force needed for safe grasping, a critical advance for agricultural robotics, food handling, and human-robot collaboration. This work bridges the gap between perception and action, addressing real-world challenges in automation. Cui’s impact is evident in the growing interest in his methods, which have been cited by researchers exploring tactile-driven control and soft robotics. His achievements highlight a commitment to practical, sensor-rich solutions that enhance robotic dexterity and safety, making him a notable voice in the evolving field of embodied AI.
Research Focus
Key Achievements
Top Papers
- 1