Xiuzhuang Zhou received the B.S. from Chengdu University of Information Technology, Chengdu, China, in 1996 and the M.Eng. and Ph.D. degrees from Beijing Institute of Technology, Beijing, China, in 2005 and 2011, respectively. He has been a Full Professor since 2020 at the Beijing University of Posts and Telecommunications, Beijing, China. His research area includes computer vision, machine learning and medical AI. He has authored more than 80 technical papers in computer vision, affective computing, and biometrics recognition. He won multiple international AI technology competitions in several top-tier AI conferences, including the NTIRE Light Field Image Super-Resolution Challenges (at CVPR 2025 and CVPR 2023), the Large-Scale Point Cloud Analysis for Urban Scenes Understanding Challenge (at ICCV 2021) and the Recognizing Families in the Wild Challenge (at IEEE FG 2021).  He is an Associate Editor for IEEE Transactions on Affective Computing, and an editorial board member for Neurocomputing (Elsevier).

Selected publications:

[1]  Yonghong Li, Shan Qu, and Xiuzhuang Zhou. “Conformal Depression Prediction,” IEEE Transactions on Affective Computing, 2025.

[2]  Yonghong Li, Zeqiang Wei, Guodong Guo, and Xiuzhuang Zhou. “MemRank: Memory-augmented similarity ranking for video-based depression severity estimation,” IEEE Transactions on Affective Computing, 2025.

[3]  Zheng Zhang, Guanchun Yin, Bo Zhang, Wu Liu, Xiuzhuang Zhou, Wendong Wang. “A semantic knowledge complementarity based decoupling framework for semi-supervised class-imbalanced medical image segmentation,” CVPR, 2025.

[4]  Zeyi Hou, Ning Lang, and Xiuzhuang Zhou. “WL-GAN: Learning to sample in generative latent space,” Information Sciences, 2025.

[5]  Ximiao Zhang, Min Xu, and Xiuzhuang Zhou. “RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection,” CVPR, 2024.

[6]  Yu Bai, Bo Zhang, Zheng Zhang, Shuo Yan, Zibo Ma, Wu Liu, Xiuzhuang Zhou, Xiangyang Gong, and Wendong Wang. “Norma: A Noise Robust Memory-Augmented Framework for Whole Slide Image Classification,” ECCV, 2024.

[7]  Min Xu, Ximiao Zhang, and Xiuzhuang Zhou. “Confidence-Calibrated Face and Kinship Verification,” IEEE Transactions on Information Forensics & Security, 2024.

[8]  Mingyue Niu, Ya Li, Jianhua Tao, Xiuzhuang Zhou, Björn W Schuller. “DepressionMLP: A Multi-Layer Perceptron Architecture for Automatic Depression Level Prediction via Facial Keypoints and Action Units,” IEEE Transactions on Circuits and Systems for Video Technology, 2024.

[9]  Zeyi Hou, Ruixin Yan, Ziye Yan, Ning Lang, and Xiuzhuang Zhou. "Energy-Based Controllable Radiology Report Generation with Medical Knowledge," International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024.

[10] Ximiao Zhang, Min Xu, Dehui Qiu, Ruixin Yan, Ning Lang, and Xiuzhuang Zhou. "Mediclip: Adapting clip for few-shot medical image anomaly detection," International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024.

[11] Zeqiang Wei, Kai Jin, Zheng Zhang, and Xiuzhuang Zhou. “Multi-label contrastive hashing,” Pattern Recognition, 2023.

[12] Zeyi Hou, Ruixin Yan, Qizheng Wang, Ning Lang, and Xiuzhuang Zhou. “Diversity-Preserving Chest Radiographs Generation from Reports in One Stage,” International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023.

[13] Xiuzhuang Zhou, Zeqiang Wei, Min Xu, Shan Qu, and Guodong Guo. “Facial Depression Recognition by Deep Joint Label Distribution and Metric Learning,” IEEE Transactions on Affective Computing, 2022.

[14] Bo Zhang, Yunpeng Tan, Hui Wang, Zheng Zhang, Xiuzhuang Zhou, Jingyun Wu, Yue Mi, Haiwen Huang, and Wendong Wang. “LSRML: A Latent Space Regularization based Meta-Learning Framework for MR Image Segmentation,” Pattern Recognition, 2022.

[15] Peng Huang, Xiuzhuang Zhou, Zeqiang Wei, and Guodong Guo. “Energy-based supervised hashing for multimorbidity image retrieval,” International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2021.

[16] Xiuzhuang Zhou, Kai Jin, Yuanyuan Shang, and Guodong Guo. "Visually interpretable representation learning for depression recognition from facial images," IEEE Transactions on Affective Computing, 2020.

[17] Xiuzhuang Zhou, Kai Jin, Qian Chen, Min Xu, and Yuanyuan Shang. "Multiple face tracking and recognition with identity-specific localized metric learning," Pattern Recognition, 2018.

[18] Haibin Yan, Jiwen Lu, and Xiuzhuang Zhou. "Prototype-based discriminative feature learning for kinship verification," IEEE Transactions on Cybernetics, 2015.

[19] Jiwen Lu, Venice Erin Liong, Xiuzhuang Zhou, and Jie Zhou. "Learning compact binary face descriptor for face recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015.

[20] Jiwen Lu, Xiuzhuang Zhou, Yap-Pen Tan, Yuanyuan Shang, and Jie Zhou. "Neighborhood repulsed metric learning for kinship verification," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014.

[21] Haibin Yan, Jiwen Lu, Weihong Deng, and Xiuzhuang Zhou. "Discriminative multi-metric learning for kinship verification," IEEE Transactions on Information Forensics and Security, 2014.

[22] Weihong Deng, Jiani Hu, Xiuzhuang Zhou, and Jun Guo. "Equidistant prototypes embedding for single sample based face recognition with generic learning and incremental learning," Pattern Recognition, 2014.

[23] Jiwen Lu, Xiuzhuang Zhou, Yuanyuan Shang, Yap-Pen Tan, and Jie Zhou. "Cost-sensitive semi-supervised discriminant analysis for face recognition." IEEE Transactions on Information Forensics & Security, 2012.

[24] Xiuzhuang Zhou, Yao Lu, Jiwen Lu, and Jie Zhou. "Abrupt motion tracking via intensively adaptive Markov chain Monte Carlo sampling," IEEE Transactions on Image Processing, 2012.

[25] Xiuzhuang Zhou, Jiwen Lu, Junlin Hu, and Yuanyuan Shang. "Gabor-based gradient orientation pyramid for kinship verification under uncontrolled environments," ACM International Conference on Multimedia, 2012.

[26] Xiuzhuang Zhou, Junlin Hu, Jiwen Lu, Yuanyuan Shang, and Yong Guan. "Kinship verification from facial images under uncontrolled conditions," ACM International Conference on Multimedia, 2011.

[27] Xiuzhuang Zhou and Yao Lu. "Abrupt motion tracking via adaptive stochastic approximation Monte Carlo sampling," CVPR, 2010.

[28] 周修庄, 鲁继文. 视觉跟踪中的马氏链蒙特卡洛方法[M]. 北京邮电大学出版社. 2018.