Shandeng Huang

Zhejiang Lab, Chengdu University of Technology

Papers

Total Citations

H-Index

About

Shandeng Huang is a rising researcher in the field of surgical robotics, with a focused interest in developing intelligent systems for robot-assisted minimally invasive surgery. His work addresses a critical challenge in the operating room: the risk of soft tissue damage caused by excessive clamping force, which surgeons cannot directly feel. To solve this, Huang pioneered a robust method for predicting tool-tissue interaction force using an Improved Sparrow Search Algorithm (ISSA) to optimize backpropagation neural networks. This innovation, detailed in his 2025 paper, offers a data-driven solution to enhance surgical safety and efficiency by enabling more precise force control. His research also extends to orthopedic applications, as seen in his 2021 work on a bone connection robotic hand designed for fracture reduction surgery. While his citation counts are currently modest—with 3 and 2 citations respectively—these early contributions signal a promising trajectory in a high-stakes field. By combining machine learning with mechanical design, Huang is laying the groundwork for smarter, safer robotic tools that could one day become standard in operating rooms worldwide.