Jintang Li's Homepage

Jintang Li (李金膛 in Chinese) Assistant Professor Institute of Artificial Intelligence Xiamen University Media Analytics & Computing Laboratory (MAC Lab) PyG Team E-mail: edisonlee [AT] xmu.edu.cn [GitHub] [Google Scholar] [DBLP] [Zhihu]

About me

I am currently an assistant professor at the Institute of Artificial Intelligence, Xiamen University. I am also affiliated with Media Analytics & Computing Laboratory (MAC Lab). Before that, I received my M.S. and Ph.D. degrees from Sun Yat-sen University in 2021 and 2025, respectively, where I was advised by Prof. Liang Chen, Prof. Wuhui Chen, and Prof. Zibin Zheng.

My research interests include:

• Trustworthy Graph Learning: reliability, fairness, etc.

• Graph Neural Networks

• Large Language Models

• Generative Recommendation

We are always recruiting undergraduate/master students. Please contact me with your CV attached if you are interested in the above topics.

PyTorch Geometric

I am a core maintainer of PyTorch Geometric (PyG), Feel free to reach out to me for support or guidance in working with PyG.

Educations

Sun Yat-sen University Ph.D in Software Engineering, from August 2021 to June 2025. Sun Yat-sen University M.S. in Electronics and Communications Engineering, from August 2019 to June 2021.

Experiences

[2022-2023] Research Intern at Ant Group, from February 2022 to June 2022. [2023-2024] Research Intern at Ant Group, from July 2023 to March 2024.

Recent news

• November 27, 2025: I joined the Institute of Artificial Intelligence, Xiamen University as an Assistant Professor.

• November 26, 2025: I won second place of Tencent Advertising Algorithm Competition (TAAC 2025).

• October 29, 2025: I was honored with the ACM China (Zhuhai Chapter) Doctoral Dissertation Award in recognition of my outstanding doctoral research in computer science.

• [ICLR 2026] September 23, 2025: I was invited to serve as a reviewer for ICLR 2026.

• [AAAI 2026] July 28, 2025: I was invited to serve as a reviewer for AAAI 2026.

• [KDD 2026] July 25, 2025: I was invited to serve as a reviewer for both KDD 2026 Research Track and Dataset & Benchmark Track.

• [LoG 2025] July 23, 2025: I was invited to serve as a reviewer for LoG 2025.

• June 21, 2025: I was honored as an Outstanding Graduating Ph.D. Student by Sun Yat-sen University.

• [TPAMI 2025] May 19, 2025: One paper has been accepted by TPAMI.

• [ICML 2025] May 1, 2025: One paper has been accepted by ICML 2025.

• [NeurIPS 2025] April 17, 2025: I was invited to serve as a reviewer for NeurIPS 2025 Dataset and Benchmark Track.

• [CIKM 2025] April 16, 2025: I was invited to join the Program Committee for CIKM 2025.

• [KDD 2025] March 4, 2025: I was invited to serve as a reviewer for KDD 2025 Dataset and Benchmark Track February.

Selected Publications

Note: * for corresponding author, # for equal contribution.
Please find my full list of publications in the following Link.

Conferences and Journals

1. Heterophily-aware Representation Learning on Heterogenerous Graphs
   Jintang Li, Zheng Wei, Yuchang Zhu, Ruofan Wu, Huizhe Zhang, Liang Chen*, Zibin Zheng.
   IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI 2025).
   [pdf] [code]

2. Measuring Diversity in Synthetic Datasets
   Yuchang Zhu, Huizhe Zhang, Bingzhe Wu, Jintang Li, Zibin Zheng, Peilin Zhao, Liang Chen, Yatao Bian.
   In Proceedings of the Forty-second International Conference on Machine Learning (ICML 2025).
   [pdf]

3. State Space Models on Temporal Graphs: A First-Principles Study
   Jintang Li#, Ruofan Wu#, Xinzhou Jin, Boqun Ma, Liang Chen, Zibin Zheng.
   In Proceedings of the Thirty-eighth Annual Conference on Neural Information Processing (NeurIPS 2024).
   [pdf] [code]

4. Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective
   Yunfei Liu#, Jintang Li#*, Yuehe Chen, Ruofan Wu, Baokun Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen.
   In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024).
   [pdf] [code]

5. One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes
   Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen*.
   In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024).
   [pdf] [code]

6. Fair Graph Representation Learning via Sensitive Attribute Disentanglement
   Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen*.
   In Proceedings of the 16th international conference on World Wide Web (WWW or TheWebConf 2024).
   [pdf] [code]

7. A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
   Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen*.
   In Proceedings of the 12th International Conference on Learning Representations (ICLR 2024).
   [pdf] [code]

8. The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation
   Yuchang Zhu, Jintang Li, Liang Chen*, Zibin Zheng.
   In Proceedings of the 17th ACM International Conference Web Search and Data Mining (WSDM 2024).
   [pdf] [code]

9. Rethinking and Simplifying Bootstrapped Graph Latents
   Wangbin Sun, Jintang Li, Liang Chen*, Bingzhe Wu, Yatao Bian, Zibin Zheng.
   In Proceedings of the 17th ACM International Conference Web Search and Data Mining (WSDM 2024).
   [pdf] [code]

10. What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
    Jintang Li#, Ruofan Wu#, Wangbin Sun, Liang Chen*, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang.
    In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023).
    [pdf] [code]

Preprints

1. Are Large Language Models In-Context Graph Learners?
   Jintang Li, Ruofan Wu, Yuchang Zhu, Huizhe Zhang, Liang Chen*, Zibin Zheng.
   arXiv, 2024.
   [pdf]

2. Revisiting and Benchmarking Graph Autoencoders: A Contrastive Learning Perspective
   Jintang Li, Ruofan Wu, Yuchang Zhu, Huizhe Zhang, Xinzhou Jin, Guibin Zhang, Zulun Zhu, Zibin Zheng, Liang Chen*.
   arXiv, 2024.
   [pdf] [code]

Projects

1. PyTorch Geometric (collaborator): Graph Neural Network Library for PyTorch.

2. GraphGallery: A gallery for benchmarking Graph Neural Networks (GNNs).

3. GreatX: A graph reliability toolbox based on PyTorch and PyTorch Geometric.

4. Awesome Graph Adversarial Learning: A curated collection of adversarial attack and defense on graph data.

5. Awesome Fair Graph Learning: Paper Lists for Fair Graph Learning (FairGL).

6. Awesome Masked Autoencoders: A collection of literature after or concurrent with Masked Autoencoder (MAE).

Rewards

I am interested in participating in AI competitions and would love to collaborate with others! Please feel free to reach out to me if you are also interested in such collaborations.

1. Tencent Advertising Algorithm Competition (TAAC 2025) [Link] - 🥈2nd place (2/2800).

2. DC 2025: The 3rd Challenge on Electromagnetic Data [Link] - 🥉3rd place.

3. WWW 2025 multimodal LLMs [Link] - 5th place (5/1643).

4. The 2nd World AI4S Prize, LLM Logical Reasoning track - 🏆1st place.

5. Car Drag Detection Challenge, IJCAI 2024 [Link], track 1 & 3 - 🥉3rd place.

6. Deepfake Speech Detection Challenge, IJCAI 2024 [Link], 🥈2nd place.

7. Medical Treatment and Public Health, Seed 2023 [Link], 🏆1st place.

8. Ant Group ATEC 2023 [Link], online track 2 & 3 - 🏆1st place, final - 🥈2nd place.

9. iFLYTEK AI development competition 2023: Social account network classification [Link], 🏆1st place.

10. iFLYTEK AI development competition 2023: New user prediction [Link], 🥈2nd place.

11. Ant Group ATEC 2022 [Link], 🥈2nd place.

12. Baidu AI Competition 2023: CVR Prediction. [Link], 🥈2nd place.

13. CAAI-BDSC 2023, Dynamic Link Prediction In Social Knowledge Graphs. [Link], 🥉3rd place.

14. Ant Group Green Computing Contest. [Link], 🥈2nd place.

15. CIKM 2022 AnalytiCup Competition: Federated Hetero-Task Learning. [Link] [Code], 🏅4th place.

16. ICDM 2022 Competition: Risk Commodities Detection on Large-Scale E-Commence Graphs. [Link] [Code], 🥉3rd place.

17. FinvCup 2022: Fraud User Risk Identification. [Link], [Code], 🏅9th place.

18. Ant Group ATEC 2021: truthworthy AI. [Link], 🥈2nd place.

19. Ant Group ATEC 2021 online, Track 2: Fraud detection of digital currency transactions. [Link], 🏅4th place.

20. Spectra Review Paper Competition 2022 (Spring) 🏆winner. [Link].

21. Spectra Review Paper Competition 2021. [Link], 🥉3rd place winner with [Introduction on Graph Adversarial Learning].

22. KDD Cup 2020, Adversarial Attacks and Defense on Academic Graph. [Link], 🥈2nd place.

Talks

1. KDD 2022 tutorial: Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection.

2. AI TIME IJCAI 2021: Understanding Structural Vulnerability in Graph Convolutional Networks (in Chinese).

Scholarship & Honors

1. National Scholarship: 2022-2023 & 2023-2024 at Sun Yat-sen University (Top 0.2%).

2. The Academic Star Nomination Award at Sun Yat-sen University (逸仙学术之星提名奖, Top 0.02%). [News]

3. Top-100 students at Sun Yat-sen University (百年校庆百名优秀学子). [News]

4. Guo Xie Birong Scholarship 2024-2025 at Sun Yat-sen University (中山大学郭谢碧蓉奖学金, Top 0.2%).

5. Outstanding Graduating Ph.D. Student of Sun Yat-sen University.

6. ACM China (Zhuhai Chapter) Doctoral Dissertation Award (ACM中国珠海分会优博奖)

Professional services

• Reviewer: AAAI, IJCAI, WWW, CIKM, WSDM, KDD, ICML, NeurIPS, ICLR, TKDD, LoG, JMLR, TPAMI etc.

Useful Links

Deadlines: ccf-ddl
CCF list: ccf.atom.im