Xiajie Zhang

Jingdong (China), Massachusetts Institute of Technology

Papers

Total Citations

H-Index

About

Xiajie Zhang is a researcher at the intersection of computer vision and human-robot interaction, with key contributions in hand pose estimation and affect-aware educational robotics. Zhang’s most cited work, "FastHand" (2021, 27 citations), introduces a monocular hand pose estimation method designed for real-time performance on embedded systems, addressing the critical need for low-latency, high-accuracy models in human-machine interaction. In "Dual Regression for Efficient Hand Pose Estimation" (2022, 9 citations), Zhang further advances this area by proposing a regression technique that balances computational efficiency with precision, enabling reliable deployment in resource-constrained environments. Beyond vision, Zhang’s research explores the nuanced role of context in child-robot interaction. The 2020 paper "Impact of Interaction Context on the Student Affect-Learning Relationship" (16 citations) challenges prevailing assumptions by demonstrating that the affect-learning link is bidirectional and dependent on agent behaviors, offering a more dynamic framework for designing educational robots. This work highlights Zhang’s ability to bridge technical innovation with psychological insight, making significant strides in both efficient computer vision and socially aware robotics.