Publications

(* indicates equal contribution)

1. Adversarial Attacks on Fairness of Graph Neural Networks. [PDF] [Code]
   Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li.
   ICLR 2024.

2. AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach. [PDF] [Code]
   Shujie Yang, Binchi Zhang, Shangbin Feng, Zhaoxuan Tan, Qinghua Zheng, Ziqi Liu, Minnan Luo.
   CIAC 2023 (Best Application Paper Finalist).

3. RELIANT: Fair Knowledge Distillation for Graph Neural Networks. [PDF] [Code]
   Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li.
   SDM 2023.

4. TwiBot-22: Towards Graph-Based Twitter Bot Detection. [PDF] [Code]
   Shangbin Feng*, Zhaoxuan Tan*, Herun Wan*, Ningnan Wang*, Zilong Chen*, Binchi Zhang*, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo.
   NeurIPS 2022 (Datasets and Benchmarks Track).

5. Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications. [PDF]
   Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li.
   SIGKDD Explorations Newsletter, 2022, 24(2): 32-47.
   A short version is accepted to FedGraph@CIKM 2022 (spotlight).

6. ELEGANT: Certified Defense on the Fairness of Graph Neural Networks. [PDF] [Code]
   Yushun Dong, Binchi Zhang, Hanghang Tong, Jundong Li.
   ArXiv preprint arXiv:2311.02757.

7. PPSGCN: A Privacy-Preserving Subgraph Sampling Based Distributed GCN Training Method. [PDF] [Code]
   Binchi Zhang, Minnan Luo, Shangbin Feng, Ziqi Liu, Jun Zhou, Qinghua Zheng.
   ArXiv preprint arXiv:2110.12906.