Papers
5
Total Citations
22
H-Index
4
About
Wa Gao is a pioneering researcher at the intersection of robotics, human-robot interaction (HRI), and intelligent filtering systems. Her work centers on two key areas: developing advanced algorithms for robotic motion control and understanding the emotional dynamics between humans and robots. Gao’s major contributions include a fast filtering algorithm inspired by vibration systems and neural information exchange, which enhances the precision of micro-motion robots, and a novel emotion recognition method for humanoid robot body movements using a PSO-BP-RMSProp neural network—a computational model that bridges robot bodily expressions with human emotional perception. Her studies on user emotions during HRI errors and human perception of robot emotional expressions, supported by survey and eye-tracking data, have been widely cited (e.g., 6 and 5 citations for her foundational works). Notably, her 2024 design study on commercial cleaning robots, integrating Kano-QFD methodology, addresses post-pandemic public safety needs, showcasing her ability to translate theoretical insights into practical applications. With over 20 citations across her most-cited papers, Gao’s research is shaping the future of emotionally intelligent and socially aware robots.
Research Focus
Key Achievements
Top Papers
- 1
- 2A Design Study on Commercial Cleaning Robots Based on Kano–QFD5 citations · 2024
- 3
- 4
- 5