Jingting Zhang

University of Rhode Island, University of Electronic Science and Technology of China

Papers

Total Citations

H-Index

About

Jingting Zhang is a rising researcher in soft robotics, human-robot interaction, and intelligent control systems. Her work bridges the gap between theoretical modeling and practical applications, with a focus on making robots safer and more responsive to human needs. Zhang’s most cited paper, “Nonlinear Dynamics Modeling and Fault Detection for a Soft Trunk Robot: An Adaptive NN-Based Approach” (2022, 16 citations), introduces a radial basis function neural network to model and detect faults in soft robots—a critical step toward reliable, flexible manipulators. She has also advanced assistive robotics through “Adaptive Coordinated Motion Planning for Lower Limb Exoskeleton Robots with a Robotic Walker” (2025, 3 citations), enhancing mobility support for users. In “Gaze Betray You: Abnormal Attention Detection from Human-Robot Interaction Dynamics” (2024, 2 citations), Zhang explores how gaze patterns can reveal lapses in attention during human-robot collaboration, with implications for autonomous driving and remote operations. Her work is notable for integrating adaptive algorithms with real-world robotic systems, earning recognition for its potential to improve safety and autonomy. With a growing citation record, Zhang is establishing herself as a key contributor to next-generation robotic systems.