Qiao Xie

Papers

Total Citations

249

H-Index

About

Dr. Qiao Xie is a leading researcher in affective computing and biomedical signal processing, with a primary focus on advancing emotion recognition technologies. Her major contributions lie in developing novel computational models for interpreting human emotional states from physiological signals. Notably, she pioneered an improved brain emotion learning model for speech emotion recognition, which has garnered 169 citations, demonstrating its significant impact on the field. Dr. Xie also made substantial advances in electroencephalogram (EEG) emotion recognition by proposing a hybrid feature extraction method in the empirical mode decomposition domain, combined with optimal feature selection via sequence backward selection. This work, cited 80 times, enables the capture of subtle, multiscale information from unstable EEG signals, enhancing recognition accuracy. Her research bridges neuroscience and machine learning, offering robust frameworks for human-computer interaction and mental health monitoring. Through these achievements, Dr. Xie has established herself as a key contributor to emotion-aware systems, with her work widely referenced by peers seeking to improve the reliability and sensitivity of affective computing applications.