I’m a Ph.D. student in the School of Computer Science and Engineering at Sun Yat-sen University (SYSU) supervised by Prof. Di Wu. Before studying at SYSU, I received my B.S. (Computer Science and Engineering) degree at Shandong University in 2023. My research centers on graph machine learning, federated learning, and their intersection. I’ve dedicated efforts to modeling relational data, aiming to develop efficient and practical solutions. Feel free to reach out to me for any discussions or questions.

📝 Publication Highlights

(* denotes the equal contribution)

• Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement [NeurIPS 2025]

  Yinlin Zhu*, Xunkai Li*, Jishuo Jia, Miao Hu, Di Wu, Meikang Qiu

• FedC4: Graph Condensation Meets Client-Client Collaboration for Efficient and Private Federated Graph Learning [CIKM 2025]

  Zekai Chen, Xunkai Li, Yinlin Zhu, Rong-Hua Li, Guoren Wang

• Federated Continual Graph Learning [KDD 2025]

  Yinlin Zhu, Miao Hu, Di Wu

• Rethinking Federated Graph Learning: A Data Condensation Perspective [IJCAI 2025]

  Hao Zhang, Xunkai Li, Yinlin Zhu, Lianglin Hu

• OpenFGL: A Comprehensive Benchmarks for Federated Graph Learning [VLDB 2025]

  Xunkai Li, Yinlin Zhu, Boyang Pang, Guochen Yan, Yeyu Yan, Zening Li, Zhengyu Wu, Wentao Zhang, Rong-Hua Li, Guoren Wang

• FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning [IJCAI 2024]

  Yinlin Zhu, Xunkai Li, Zhengyu Wu, Di Wu, Miao Hu, Rong-Hua Li

• FedGTA: Topology-aware Averaging for Federated Graph Learning [VLDB 2024]

  Xunkai Li, Zhengyu Wu, Wentao Zhang, Yinlin Zhu, Rong-Hua Li, Guoren Wang