Qingnan Gao

University of Science and Technology Beijing

Papers

Total Citations

H-Index

About

Qingnan Gao is a researcher at the forefront of affective computing and human-robot interaction, with a primary focus on speech emotion recognition. His work addresses a critical challenge in robotics: enabling machines to perceive and respond to human emotional states for more natural, empathetic communication. In his highly cited 2021 survey on intelligent robots in speech emotion recognition, Gao provides a comprehensive overview of the field’s evolution, synthesizing key methodologies and highlighting persistent challenges. This survey has become a foundational reference, garnering 2 citations and serving as a valuable roadmap for researchers seeking to advance affective interfaces. Gao’s contributions lie in systematically mapping the intersection of speech signal processing, machine learning, and robotic systems, emphasizing how emotional awareness can transform human-robot collaboration. His research underscores the importance of robust feature extraction, multimodal integration, and real-time processing for practical deployment. By bridging technical innovation with human-centered design, Qingnan Gao is helping to shape a future where robots not only understand words but also the emotions behind them.