| 2026 | AAAI | FairGSE: Fairness-Aware Graph Neural Network Without High False Positive Rates. | Zhenqiang Ye, Jinjie Lu, Tianlong Gu, Fengrui Hao, Xuemin Wang |
| 2026 | DASFAA | Mitigating Popularity Bias for Two-Sided Fairness via Dual-Teacher Distillation in Recommendation. | Chao Guo, Xuemin Wang, Chuangying Zhu, Jialung Liang, Heng Yang, Liang Chang |
| 2025 | DASFAA | FairDP-GNN: Graph Neural Network with Group Fairness and Differential Privacy. | Fengrui Hao, Shiyi Zhao, Tianlong Gu, Xuemin Wang, Xiaoli Liu, Yuanfeng Liu |
| 2025 | ICASSP | BIGFR: Bridging Individual and Group Fairness in Recommendation Systems. | Yaorui Gan, Xuemin Wang, Tieyuan Liu, Liang Chang, Qicang Gen, Yu Zeng |
| 2025 | ICDE | Towards Fair Graph Neural Networks via Graph Counterfactual Without Sensitive Attributes. | Xuemin Wang, Tianlong Gu, Xuguang Bao, Liang Chang |
| 2025 | MICCAI | MVP-LLMs: Optimizing Intervention Timing and Subsequent Decision Support for Mechanical Ventilation Parameter Control Using Large Language Models. | Teqi Hao, Xiaoyu Tan, Bin Li, Xuemin Wang, Chao Qu, Yinghui Xu, Xihe Qiu |
| 2025 | TrustCom | IAGNN: Mitigating Quantity and Topological Imbalance for Fair Graph Learning. | Yangqi Liu, Xuemin Wang, Liang Chang, Heng Yang |
| 2024 | ACML | Counterfacual Fairness for Graph Neural Networks with Limited and Privacy Protected Sensitive Attributes. | Xuemin Wang, Lei Wang, Tianlong Gu, Xuguang Bao |
| 2023 | DASFAA | Fair and Privacy-Preserving Graph Neural Network. | Xuemin Wang, Tianlong Gu, Xuguang Bao, Liang Chang |
| 2016 | ICNC | Sensitivity analysis for time domain response of transmission lines based on the precise integration method. | Xiaoke Chen, Jie Zeng, Hao Zhou, Jinquan Zhao, Xuemin Wang |
| 2016 | ICNC | An online measuring method of impedance parameters of asymmetric transmission lines. | Jianhua Yin, Jinquan Zhao, Xuemin Wang, Huanrui Liu, Yan Gao |