Yating Zhang

Sichuan University, Hefei University of Technology

Papers

Total Citations

H-Index

About

Yating Zhang is a researcher whose work sits at the intersection of artificial intelligence, human-computer interaction, and robotics. Her key research areas include deep learning for affective computing and reinforcement learning for autonomous robotic systems. In her 2022 study on public emotion network communication, Zhang developed a deep learning framework to model and optimize how emotions propagate through digital networks, offering new insights for intelligent HCI systems. Her 2021 work on surgical robotics is particularly notable, where she applied a HER-DDPG reinforcement learning algorithm to enable a 7-DOF robot arm to autonomously plan dynamic trajectories, avoiding obstacles while efficiently reaching target points—a significant step toward more intelligent and autonomous surgical assistance. Though early in her career, with her most-cited papers garnering 2-3 citations, Zhang’s contributions demonstrate a forward-looking approach to integrating AI with real-world applications, from understanding collective emotional dynamics to advancing precision in robotic surgery. Her work signals a promising trajectory in bridging computational intelligence with human-centered technologies.