I am currently a 4th-year undergraduate student at Zhejiang University and an incoming Ph.D student at Hongkong University working with Prof. Chao Huang . My research interests include graph representation learning, LLM+graph and its cross-disciplinary applications (e.g. RAG with KG). For more details, please refer to my CV.

You can contact me at : fantianyu {at} zju [dot] edu [dot] cn

[ Google Scholar ] [ GitHub ] [ ORCID ]


Research Experiences


DMML-Lab, Arizona State University        (March. 2023---Sept. 2023)
Research Intern (remote), advised by Prof. Huan Liu & Prof. Kaize Ding

  • work on graph life-long learning, dividing forgetting on graph into benign and malignant, and using prompt-tuning to relieve malignant forgetting.


    • AI-Net, Zhejiang University        (Dec. 2022---March. 2023)
    Research Intern, advised by Prof. Yang Yang

  • work on graph pre-training&fine-tuning, with particular attention to narrow the gap when pre-trained models are applied to downstream tasks.


    • AI Lab, Westlake University        (June. 2022---Nov. 2022)
    Research Intern, advised by Prof. Stan Z.Li

  • work on knowledge distillation, analyzed the shortage during distillation from GNN to MLP in the spatial domains and proposed a framework to improve it.
  • work on self-supervised learning, aimed at combining self-supervised tasks on graph in a fully automated way.

    • Publications


    Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks
    Tianyu Fan*, Lirong Wu*, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li
    The Twelfth International Conference on Learning Representations (ICLR'24)


    Narrow the Gap between Graph Pre-training and Fine-tuning
    Yifei Sun, Qi Zhu, Yang Yang, Chunping Wang, Tianyu Fan, Jiajun Zhu, Lei Chen
    Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI’24)


    Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting it into MLPs: An Effective GNN-to-MLP Distillation Framework
    Lirong Wu, Haitao Lin, Yufei Huang, Tianyu Fan, Stan Z. Li
    Proceedings of the 37th Conference on Artificial Intelligence (AAAI'23)


    Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillation
    Lirong Wu, Yufei Huang, Haitao Lin, Zicheng Liu, Tianyu Fan, Stan Z. Li
    arXiv preprint arXiv:2210.02099

    Selected Awards

  • 2022, Zhejiang University Second-class Scholarship (4/123)
  • 2022, Zhejiang Provincial Government Scholarship (6/123)
  • 2022, Liyue Venture Capital Student Scholarship (10/123)
  • 2021, Zhejiang University Second-class Scholarship (30/735)
  • 2021, Xiaomi Scholarship (10/735)

    • Selected Projects

  • awesome-spatio-temporal-graph (owner)
  • awesome-graph-self-supervised-learning (contributer)