About

Lun Xie is a pioneering researcher at the intersection of artificial psychology, human-robot interaction, and industrial cybersecurity. Her work fundamentally explores how robots can understand, express, and regulate emotions—creating machines that don't just compute, but empathize. Xie’s major contributions include developing cognitive emotional regulation models based on Hidden Markov Models (HMM) and Gross emotion regulation theory, enabling robots to dynamically adjust their emotional responses during interaction. She has also pioneered the integration of personality models (Five Factors Model) into robotic emotional expression, making interactions more natural and personalized. In the security domain, Xie has advanced intrusion detection for industrial robotic arms using hybrid PSO-H-SVM methods and proposed detection mechanisms for targeted attacks on heavy-duty robots. Her most cited work (18 citations) addresses the overlooked cybersecurity risks in the fourth industrial revolution’s robotic systems. With over a dozen publications spanning from 2011 to 2023, Xie’s research has accumulated significant impact, particularly through her foundational work on artificial psychology in China and her innovative reinforcement emotion-cognition systems for intelligent learning environments. Her interdisciplinary approach bridges cognitive science, robotics, and cybersecurity.

Research Focus

Key Achievements

8
H-Index
21
Papers
152
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Research on a PSO-H-SVM-Based Intrusion Detection Method for Industrial Robotic Arms
18 citations · 2022
📈 Most Prolific Year: 2017 (2 Papers)
🤝 Key Collaborators: 37
🏛 Institutions: University of Science and Technology Beijing, Beijing Information Science & Technology University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago