Minjia Li

University of Science and Technology Beijing

Papers

Total Citations

H-Index

About

Minjia Li is a pioneering researcher at the intersection of affective computing, human-robot interaction, and cognitive systems. Her work focuses on developing intelligent learning environments where robots can model, regulate, and respond to human emotions in real time. In her highly cited 2019 paper, "Reinforcement Emotion-Cognition System: A Teaching Words Task" (10 citations), Li introduced a groundbreaking framework that integrates emotion regulation with quantitative motivation, enabling robots to adapt their teaching strategies based on a learner’s emotional state. This bottom-up collaboration model has significant implications for personalized education and assistive robotics. Her earlier 2018 study, "Emotional Contagion System By Perceiving Human Emotion Based on Physiological Signals" (5 citations), demonstrated how wearable sensors can capture physiological cues—such as heart rate or skin conductance—to allow robots to "catch" and mirror human emotions, fostering more natural and empathetic interactions. By bridging emotion recognition with robotic cognition, Li’s work lays the foundation for emotionally intelligent machines that can support learning, therapy, and social engagement, making her a key contributor to the future of human-centered AI.