Papers
2
Total Citations
51
H-Index
1
About
Ziting Guo is a leading researcher in the field of acoustic sensing and human–machine interaction (HMI), with a focus on developing intelligent auditory systems for robotics. Her work centers on creating highly sensitive, omnidirectional acoustic sensors that enable robots to perceive and interpret sound with unprecedented accuracy, even in noisy environments. Guo’s most-cited paper, “A Highly‐Sensitive Omnidirectional Acoustic Sensor for Enhanced Human–Machine Interaction” (2024, 50 citations), introduces a novel sensor design that overcomes the longstanding challenge of tracking sound sources from all directions, significantly advancing the naturalness and efficiency of robot communication. Building on this, her 2025 study on deep learning-assisted acoustic sensors for real-time emotion recognition marks a pioneering step toward emotionally intelligent robots, capable of responding to human affective states. With her contributions bridging sensor engineering and artificial intelligence, Guo is shaping the future of auditory robotics, where machines can not only hear but also understand and empathize—a critical leap for applications in healthcare, service robotics, and collaborative automation.
Research Focus
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Top Papers
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