I am currently a research fellow at the School of Computing, National University of Singapore, working under the supervision of Prof. Xiaokui Xiao. I obtained my Ph.D. degree in June 2025 from the Gaoling School of Artificial Intelligence, Renmin University of China, under the guidance of Prof. Zhewei Wei. Between October 2024 and May 2025, I was a visiting student at the Technical University of Munich, where I collaborated with Prof. Stephan Günnemann. Prior to my Ph.D., I earned a B.E. degree in Software Engineering from the School of Computer Science at Central South University in June 2020.
My research focuses on Spectral Graph Neural Networks (GNNs), particularly leveraging spectral properties to enhance GNN performance and interpretability. I am also exploring Graph Transformers, combining attention mechanisms with graph models for more efficient graph-based data processing. Additionally, I am passionate about AI for Science (AI4Science), applying machine learning techniques to accelerate scientific discovery in fields like materials science, biology, and chemistry.
🔥 News
- 2025.05: We are excited to introduce a new benchmark for Directed Graph Link Prediction, DirLinkBench.
- 2024.01: Our paper was accepted at TheWebConf 2024 and selected for oral presentation.
📝 Publications
-
PolyFormer: Scalable Node-wise Filters via Polynomial Graph Transformer. [Paper][Code]
Jiahong Ma, Mingguo He, Zhewei Wei.
In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. (KDD 2024) -
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials. [Paper][Code]
Mingguo He,Zhewei Wei, Shikun Feng, Zhengjie Huang, Weibin Li, Yu Sun, Dianhai Yu.
In Proceedings of the ACM Web Conference 2024. (TheWebConf 2024, Oral 9.4%) -
Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited. [Paper][Code]
Mingguo He, Zhewei Wei, Ji-Rong Wen.
In the 36th Conference on Neural Information Processing Systems. (NeurIPS 2022, Oral 1.8%) -
BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation. [Paper][Code]
Mingguo He, Zhewei Wei, Zengfeng Huang, Hongteng Xu.
The 35th Conference on Neural Information Processing Systems. (NeurIPS 2021) -
Approximate Graph Propagation. [Paper][Code]
Hanzhi Wang, Mingguo He, Zhewei Wei, Sibo Wang, Ye Yuan, Xiaoyong Du, Ji-Rong Wen.
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. (KDD 2021) -
Rethinking Link Prediction for Directed Graphs. [Paper][Code]
Mingguo He, Yuhe Guo, Yanping Zheng, Zhewei Wei, Stephan Günnemann, Xiaokui Xiao
ArXiv. (Preprint)
🎖 Honors and Awards
- 2024 National Scholarship for Doctoral Students
- 2020 Provincial Excellent Graduates
- 2018 National Scholarship for Undergraduate Students
📖 Educations
- 2020.09 - 2025.06: Ph.D. in Artificial Intelligence from the Gaoling School of Artificial Intelligence, Renmin University of China, under the supervision of Prof. Zhewei Wei.
- 2024.10 - 2025.03: Visiting researcher at the Technical University of Munich, collaborating with Prof. Stephan Günnemann.
- 2016.09 - 2020.06: Bachelor of Engineering in Software Engineering from the School of Computer Science, Central South University.
💼 Services
I serve(d) as a program committee member/reviewer for:
- Conference on Neural Information Processing Systems (NeurIPS 22/23/24/25)
- International Conference on Machine Learning (ICML 23/24/25)
- International Conference on Learning Representations (ICLR 24/25)
- International World Wide Web Conference (TheWebConf 24/25)
- Learning on Graphs Conference (LoG 24/25)
- Association for the Advancement of Artificial Intelligence Conference (AAAI 25/26)
- Web Search and Data Mining Conference (WSDM 23/24/25)
- IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI journal)
- IEEE Transactions on Knowledge and Data Engineering (TKDE journal)