Wu, Chenrui, Haishuai Wang, Xiang Zhang, Chengqi Zhang, and Jiajun Bu. "Efficient Personalized Adaptation for Physiological Signal Foundation Model." In Forty-second International Conference on Machine Learning (ICML 2025).
Taida Li, Yujun Yan, Wenzhan Song, and Xiang Zhang. Optimal EEG Channel Selection for Alzheimer’s Disease Detection: An Exhaustive Analysis. Brain-Machine Interface Workshop, IEEE SMC 2025.
Nan Huang, Alexizdar Tzallas, Zihuai He and Xiang Zhang. Comparative Analysis of Foundation Models for EEG-based Alzheimer's Disease Detection. IJCNN 2025.
Manqing Dong, Lina Yao, Xianzhi Wang, Boualem Benatallah, Xiang Zhang, and Quan Z. Sheng. Dual-stream Self-Attentive Random Forest for False Information Detection. International Joint Conference on Neural Networks (IJCNN 2019), Budapest, Hungary, July 14 - 19, 2019.
Xiaodong Ning, Lina Yao, Xianzhi Wang, Boualem Benatallah, Shuai Zhang, and Xiang Zhang. Data-Augmented Regression with Generative Convolutional Network. The 19th International Conference on Web Information Systems Engineering WISE(2018), Dubai, United Arab Emirates, November 12 - 15, 2018.
Xiaofeng Liu, Zhihong Liu, Jie Li, and Xiang Zhang. "Semi-supervised contrastive learning for time series classification in healthcare." IEEE Transactions on Emerging Topics in Computational Intelligence 9, no. 1 (2024): 318-331.
Lei Bai, Lina Yao, Xianzhi Wang, Can Li, and Xiang Zhang. Deep Spatial-Temporal Sequence Modeling for Multi-Step Passenger Demand Prediction. Future Generation Computer Systems (FGCS) (2020).
Weitao Xu, Xiang Zhang, Chengwen Luo, Lina Yao, Jiangqiang Li, Zhong Ming, and Bo Wei. A Multi-view CNN-based Acoustic Classification System for Automatic Animal Specie Identification. Ad Hoc Networks.
Chaoran Huang, Lina Yao, Xianzhi Wang, Boualem Benatallah, and Xiang Zhang. Software Expert Discovery via Knowledge Domain Embeddings in a Collaborative Network. Pattern Recognition Letter (PRL).
Xiang Zhang, Computer Science & Engineering, Faculty of Engineering, UNSW, 2020. Data-Efficient Deep Representation Learning for Brain-Computer Interface and Its Applications. (Ph.D. Thesis)