Jing

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About

Jing’s research lies at the intersection of human-robot interaction, affective computing, and smart home technologies, with a particular focus on enhancing eldercare through emotionally intelligent systems. In their most-cited work, “Cognitive Emotion Model for Eldercare Robot in Smart Home” (2015, 4 citations), Jing pioneered a framework that enables robots to recognize and respond to human emotions by integrating Gabor filters, Local Binary Pattern (LBP) algorithms, and k-Nearest Neighbor (KNN) classifiers for facial expression analysis. This contribution addresses a critical gap in assistive robotics—enabling machines to perceive and model emotional states in real-world, domestic environments. By embedding cognitive emotion models into smart home ecosystems, Jing’s work lays the groundwork for more empathetic, adaptive caregiving robots that can improve the quality of life for aging populations. Though early in their citation trajectory, this foundational study demonstrates a clear vision for human-centered AI, where robots not only assist but also understand the emotional needs of their users. Jing’s research continues to inspire advances in affective robotics and ambient assisted living.