Zihan Luo 罗子涵

Zihan Luo 罗子涵

Ph.D Candidate of HUST

Hello, I am Zihan Luo, a final-year CS Ph.D. candidate at Huazhong University of Science and Technology (HUST) , where I am fortunate to be supervised by Professor Hong Huang (黄宏) and Principal Researcher Jianxun Lian (练建勋) from Microsoft Research Asia . Before that, I received my Bachelor degree in Electronic Engineering from HUST in 2020, and was fortunate to work closely with Professor Rui Yin (尹睿) from University of Florida .

My research interests mainly include large language models and graph data mining, especially on topics like fairness and bias. I have published several papers at the top international AI conferences and journals with .

🔥 News

  • [2025.10]:  🎉🎉 GraphInstruct is accepted by Frontiers of Computer Science (CCF-T1). Please check out!
  • [2024.11]:  🎉🎉 One paper on GNN hybrid fairness is accepted by KDD 2025 (CCF-A), accept rate 19%.
  • [2024.09]:  🎉🎉 One paper on graph fairness attacks is accepted by NeurIPS 2024 (CCF-A), accept rate 25.8%.

📝 Publications

  • [Frontiers of Computer Science] Zihan Luo, Xiran Song, Hong Huang, Jianxun Lian, Chenhao Zhang, Jinqi Jiang, Xing Xie, Hai Jin. GraphInstruct: Empowering Large Language Models with Graph Understanding and Reasoning Capability. In Frontiers of Computer Science (FCS), 2025. (CCF-T1) [PAPER] [CODE]

  • [KDD’25] Zihan Luo, Hong Huang, Jianxun Lian, Xiran Song, Hai Jin. Towards Controllable Hybrid Fairness in Graph Neural Networks. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025. (CCF-A) [PAPER]

  • [NeurIPS’24] Zihan Luo, Hong Huang, Yongkang Zhou, Jiping Zhang, Nuo Chen, Hai Jin. Are Your Models Still Fair? Fairness Attacks on Graph Neural Networks via Node Injections. In Annual Conference on Neural Information Processing Systems (NeurIPS), 2024. (CCF-A) [PAPER] [CODE] [AI-TIME]

  • [NeurIPS’23] Zihan Luo, Hong Huang, Jianxun Lian, Xiran Song, Xing Xie, Hai Jin. Cross-links Matter for Link Prediction: Rethinking the Debiased GNN from a Data Perspective. In Annual Conference on Neural Information Processing Systems (NeurIPS), 2023. (CCF-A) [PAPER] [CODE]

  • [WWW’23] Xiran Song, Jianxun Lian, Hong Huang, Zihan Luo, Wei Zhou, Xue Lin, Mingqi Wu, Chaozhuo Li, Xing Xie, Hai Jin. xGCN: An Extreme Graph Convolutional Network for Large-scale Social Link Prediction. In ACM Web Conference (WWW), 2023. (CCF-A) [PAPER] [CODE] [Youtube]

  • [Journal of Biomedical Informatics] Rui Yin*, Zihan Luo*, Pei Zhuang, Chee Keong Kwoh, Zhuoyi Lin. ViPal: A Framework for Virulence Prediction of Influenza Viruses with Prior Viral Knowledge Using Genomic Sequences. In Journal of Biomedical Informatics (JBI), 2023. (CCF-C) [PAPER] [CODE]

  • [WSDM’22] Zihan Luo, Jianxun Lian, Hong Huang, Xing Xie, Hai Jin. Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks. In ACM International Conference on Web Search and Data Mining (WSDM), 2022. (CCF-B) [PAPER] [CODE]

  • [Bioinformatics] Rui Yin, Zihan Luo, Pei Zhuang, Zhuoyi Lin, Chee Keong Kwoh. VirPreNet: A Weighted Ensemble Convolutional Neural Network for the Virulence Prediction of Influenza A Virus Using All Eight Segments. In Bioinformatics, 2021. (CCF-B) [PAPER] [CODE]

🎖 Honors and Awards

  • National Scholarship, 2025.09.
  • Academic Scholarship, 2020.09, 2021.09, 2022.09, 2023.09.
  • Huawei Scholarship, 2022.06, 2025.05.
  • Tencent Scholarship, 2022.03.
  • Finalist Award (Top 1%) at The Mathematical Contest in Modeling 2019.

💻 Internships

  • 2024.09 - 2025.03, Zhipu AI , Beijing, China.
    • Internship on LLM Alignment for Machine Learning Engineering.
    • Mentor: Zhenyu Hou

💬 Service

Program Committee Members

Transactions Reviewer

  • Reviewer for FCS
  • Reviewer for TOIT