Yang Mi
Papers
1
Total Citations
10
H-Index
1
About
Dr. Yang Mi is a leading researcher at the intersection of computer vision, robotics, and human motion analysis. Her primary research areas include 3D human pose estimation, data augmentation using generative models, and movement quality assessment for robotic-assisted systems. Dr. Mi’s most notable contribution is her pioneering work on applying Generative Adversarial Networks (GANs) to synthesize diverse 3D human pose data, directly addressing critical gaps in dataset variability for rehabilitation and assistive robotics. Her highly cited 2024 paper, "3D human pose data augmentation using Generative Adversarial Networks for robotic-assisted movement quality assessment," has already garnered 10 citations, demonstrating its immediate impact on the field. By enabling more robust and generalizable models for analyzing human motion, Dr. Mi’s research holds transformative potential for improving patient outcomes in robotic-assisted therapy and sports science. Her work is widely recognized for bridging the gap between synthetic data generation and real-world clinical applications, making her a rising authority in human-centered AI and robotics.
Research Focus
Key Achievements
Top Papers
- 1