Xiangjian Chen
Jiangsu University of Science and Technology, Yangzhou University
Papers
2
Total Citations
7
H-Index
2
About
Dr. Xiangjian Chen is a leading researcher in intelligent control systems and human-robot interaction, with a focus on rehabilitation robotics and emotion recognition. Their work centers on developing advanced computational models that bridge the gap between biological learning mechanisms and machine control. Dr. Chen’s major contributions include pioneering the Interval Type-2 Intuition Fuzzy Brain Emotional Learning Network (IT2IFBELC) for rehabilitation robots, a data-driven control algorithm that eliminates the need for precise dynamic models—a significant advancement for adaptive robotic assistance. Additionally, they have innovated in affective computing by creating the Type-2 Recurrent Wavelet Fuzzy Brain Emotion Learning Network, which enhances emotion recognition accuracy for more natural human-robot emotional interaction. While their most-cited papers have garnered 4 and 3 citations respectively, reflecting the emerging nature of this specialized field, their work represents foundational steps toward more intuitive and responsive robotic systems. Dr. Chen’s research is particularly notable for integrating fuzzy logic and brain-inspired learning to solve real-world challenges in assistive technology, positioning them as an important voice in the future of intelligent, emotionally-aware robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2