Shiqing Zhang
Papers
2
Total Citations
37
H-Index
2
About
Shiqing Zhang is a leading researcher in affective computing and intelligent human-robot interaction, with a focus on speech emotion recognition and service robotics. His pioneering work on speech emotion recognition for human-robot interaction, notably his 2013 paper on using an enhanced Kernel Isomap to reduce high-dimensional speech features, has garnered 27 citations and laid critical groundwork for machines to understand human emotional expressions. More recently, Zhang has advanced practical applications of deep learning in robotics, designing a supermarket service robot based on deep convolutional neural networks (DCNNs) that integrates hardware and software to streamline shopping and reduce labor costs—a 2020 paper with 10 citations showcasing real-world deployment. His research bridges the gap between theoretical emotion modeling and tangible robotic assistance, making significant contributions to both the science of affective computing and the engineering of autonomous service systems. Zhang’s work continues to inspire students and researchers exploring how machines can perceive human emotions and interact naturally in everyday environments.
Research Focus
Key Achievements
Top Papers
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