Haiqi Zhu
Papers
1
Total Citations
3
H-Index
1
About
Dr. Haiqi Zhu is a rising leader in multimodal human pose estimation and human-robot interaction, with a focus on advancing assistive technologies for healthcare and rehabilitation. Their most-cited work, "Meta-Transfer-Learning-Based Multimodal Human Pose Estimation for Lower Limbs" (2025, 3 citations), introduces a novel framework that combines meta-learning and transfer learning to achieve highly accurate, personalized pose estimation for lower limbs. This breakthrough addresses critical challenges in interactive systems, enabling seamless control of cooperative robots and wearable exoskeletons by adapting to individual users' movements in real time. By improving the reliability of human pose estimation in dynamic environments, Dr. Zhu’s research directly enhances the performance of healthcare monitoring equipment and assistive devices. Though early in their career, this work demonstrates significant potential for impact, laying the groundwork for more intuitive and adaptive human-machine interfaces. Dr. Zhu’s contributions are poised to transform rehabilitation robotics and personalized healthcare, offering a path toward safer, more responsive assistive technologies that adapt to the unique needs of each user.
Research Focus
Key Achievements
Top Papers
- 1