Jingru Pan
Papers
1
Total Citations
14
H-Index
1
About
Jingru Pan is a pioneering researcher at the intersection of artificial intelligence, social robotics, and public health. Her work focuses on designing emotionally intelligent robotic systems that can meaningfully interact with humans, particularly for health interventions. Pan’s most notable contribution is her 2024 paper, "Combining style generative adversarial networks with particle swarm optimisation-support vector regression to design affective social robot for public health intervention," which has already garnered 14 citations—a strong indicator of its early impact. In this study, she introduced a novel framework that integrates generative adversarial networks (GANs) for robot aesthetics with advanced machine learning optimization to create robots capable of recognizing and responding to human emotional states. This approach not only advances human-robot interaction but also offers scalable solutions for public health challenges, such as mental health support or health education. Pan’s work stands out for its interdisciplinary rigor, blending computer science, design, and behavioral science. Her research is particularly relevant for students and researchers interested in affective computing, social robotics, and the ethical deployment of AI in healthcare. With her innovative methods and growing citation record, Jingru Pan is establishing herself as a key voice in the future of empathetic technology.
Research Focus
Key Achievements
Top Papers
- 1