Zhiling Tan

University of Science and Technology Beijing

Papers

Total Citations

H-Index

About

Zhiling Tan is a researcher whose work sits at the compelling intersection of affective computing, human-robot interaction, and physiological signal processing. Their primary research focus is on enabling machines to perceive and respond to human emotions, with a particular emphasis on developing systems that can achieve emotional contagion—where a robot’s emotional state is dynamically influenced by the human it interacts with. Tan’s most cited work, "Emotional Contagion System By Perceiving Human Emotion Based on Physiological Signals" (2018, 5 citations), introduces a novel framework that leverages wearable sensors to capture physiological signals—such as heart rate or skin conductance—to recognize human emotional states. This information is then used to drive a robot’s own emotional responses, creating a more natural and empathetic interaction loop. While the citation count for this foundational paper is modest, it represents an important early step in bridging the gap between passive emotion recognition and active, responsive robotic behavior. Tan’s contributions are particularly relevant for researchers exploring socially assistive robotics, affective interfaces, and the design of emotionally intelligent autonomous systems.