Welcome! I am currently a PhD candidate at the University of New South Wales, supervised by Professor Wenjie Zhang, Professor Xuemin Lin, and Professor Ying Zhang.
My research interests include large dynamic graph processing, temporal graph neural networks, LLM for dynamic graphs, and multi-agent systems.
📣📣 We provide a comprehensive survey and introduce a new perspective for discussing Self-Evolving Agents as Dynamic Graph Transformation on GitHub. We welcome contributions from the community to help expand and improve our survey 🤗!
📣📣 We also maintain a curated list of papers on dynamic graph learning on GitHub. If you’re interested, we'd love to have your contributions!
🔥 News (2026 Onwards)
- 2026.07: I will serve as an Area Chair for LoG 2026. 🌟🌟
- 2026.06: Our paper Self-Evolving Agents as Dynamic Graph Transformation: A Survey and New Perspective is now available on ResearchGate. 🚀🚀
- 2026.05: One paper is accepted to the SIGKDD 2026. 👏👏
- 2026.01: One paper is accepted to the Web Conference 2026. 👏👏
- 2026.01: Happy New Year! 🎊🎊
🔖 Preprints
2. Self-Evolving Agents as Dynamic Graph Transformation: A Survey and New Perspective [PDF]
Yuanyuan Xu, Wenjie Zhang, Yin Chen, Xuemin Lin, Ying Zhang
1. AI-Empowered Catalyst Discovery: A Survey from Classical Machine Learning Approaches to Large Language Models [PDF]
Yuanyuan Xu, Hanchen Wang, Wenjie Zhang, Lexing Xie, Yin Chen, Flora Salim, Ying Zhang, Justin Gooding, Toby Walsh
📝 Publications
*: Co-first author; #: Corresponding author.* and # also denote the student I mentored.
19. Mitigating Anomaly Hallucination: A Model-Agnostic Framework for Unsupervised Anomaly Detection on Dynamic Graphs
Yingxuan Li, Yuanyuan Xu#, Xuemin Lin, Ying Zhang
📍 SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026)
18. Temporal Bipartite Graph Representation Learning for Behavior Anomaly Detection
Yu Kong, Yuanyuan Xu#, Dong Wen, Yu Zhang, Binghao Li, and Wenjie Zhang
📍 FLINS-ISKE 2026
17. Exploring Sequential Dynamics on Temporal Graphs via Composite Filtering [PDF]
Yuanyuan Xu, Danni Wu, Xuemin Lin, Dong Wen, Wenjie Zhang, Lei Chen, Ying Zhang
📍 The Web Conference (WWW 2026)
16. Understanding Evolving Graph Structures for Large Discrete-Time Dynamic Graph Representation [PDF]
Danni Wu*, Yuanyuan Xu*, Xuemin Lin, Wenjie Zhang, Ying Zhang
📍 Proceedings of the VLDB Endowment (VLDB 2026)
15. Unlocking Multi-Modal Potentials for Link Prediction on Dynamic Text-Attributed Graph Representation [PDF]
Yuanyuan Xu, Wenjie Zhang, Ying Zhang, Xuemin Lin, Xiwei Xu
📍 Annual AAAI Conference on Artificial Intelligence (AAAI 2026) 💡 Oral, Top 4%
14. UniDyG: A Unified and Effective Representation Learning Approach for Large Dynamic Graphs [PDF]
Yuanyuan Xu, Wenjie Zhang, Xuemin Lin, Ying Zhang
📍 IEEE Transactions on Knowledge and Data Engineering
13. Assessing Solar-to-PV Power Conversion Models: Physical, ML, and Hybrid Approaches Across Diverse Scales [PDF]
Caixia Li, Yuanyuan Xu, Minglang Xie, Pengfei Zhang, Bohan Zhang, Bo Xiao, Sujun Zhang, Ziheng Liu, Wenjie Zhang, Xiaojing Hao
📍 Energy Journal
12. Ranking on Dynamic Graphs: An Effective and Robust Band-Pass Disentangled Approach [PDF]
Yingxuan Li, Yuanyuan Xu#, Xuemin Lin, Wenjie Zhang, Ying Zhang
📍 The Web Conference (WWW 2025)
11. Fast and Accurate Temporal Hypergraph Representation for Hyperedge Prediction [PDF]
Yuanyuan Xu, Wenjie Zhang, Ying Zhang, Xiwei Xu, Xuemin Lin
📍 SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025)
10. TimeSGN: Scalable and Effective Temporal Graph Neural Network [PDF]
Yuanyuan Xu, Wenjie Zhang, Ying Zhang, Maria Orlowska, Xuemin Lin
📍 IEEE International Conference on Data Engineering (ICDE 2024)
9. Scalable and Effective Temporal Graph Representation Learning With Hyperbolic Geometry [PDF]
Yuanyuan Xu, Wenjie Zhang, Xiwei Xu, Binghao Li, Ying Zhang
📍 IEEE Transactions on Neural Networks and Learning Systems
8. Query2gmm: Learning representation with Gaussian mixture model for reasoning over knowledge graphs [PDF]
Yuhan Wu*, Yuanyuan Xu*, Wenjie Zhang, Xiwei Xu, Ying Zhang
📍 The Web Conference (WWW 2024) 💡 Oral
7. Billion-Scale Bipartite Graph Embedding: A Global-Local Induced Approach [PDF]
Xueyi Wu*, Yuanyuan Xu*, Wenjie Zhang, Ying Zhang
📍 Proceedings of the VLDB Endowment (VLDB 2024)
6. A Holistic Approach for Answering Logical Queries on Knowledge Graphs [PDF]
Yuhan Wu*, Yuanyuan Xu*, Xuemin Lin, Wenjie Zhang
📍 IEEE International Conference on Data Engineering (ICDE 2023)
5. Class-aware tiny object recognition over large-scale 3D point clouds
Jialin Li, Sarp Saydam, Yuanyuan Xu, Boge Liu, Binghao Li, Xuemin Lin, Wenjie Zhang
📍 Neurocomputing
4. Learning Accurate Label-Specific Features From Partially Multilabeled Data
Tiantian Xu, Yuanyuan Xu, Shiyu Yang, Binghao Li, Wenjie Zhang
📍 IEEE Transactions on Neural Networks and Learning Systems
3. Unsupervised cross-view feature selection on incomplete data
Yuanyuan Xu, Yu Yin, Jun Wang, Jinmao Wei, Jian Liu, Lina Yao, Wenjie Zhang
📍 Knowledge-Based Systems
2. To avoid the pitfall of missing labels in feature selection: A generative model gives the answer [PDF]
Yuanyuan Xu, Jun Wang, Jinmao Wei
📍 Association for the Advancement of Artificial Intelligence (AAAI 2020)
1. Semi-supervised multi-label feature selection by preserving feature-label space consistency
Yuanyuan Xu, Jun Wang, Shuai An, Jinmao Wei, Jianhua Ruan
📍 ACM international conference on information and knowledge management (CIKM 2018)
💻 Academic Services
Conference Organizer:
- Session Chair, ACM The Web Conference (WWW): 2026;
- Session Chair, Australasian Database Conference: 2025.
Area Chair:
- Learning on Graphs Conference: 2026.
Program Committee Member:
- International Joint Conference on Artificial Intelligence (IJCAI): 2021, 2022, 2024, 2025;
- Annual Conference on Neural Information Processing Systems (NeurIPS): 2024, 2025;
- International Conference on Machine Learning (ICML): 2025;
- ACM SIGKDD: 2025, 2026;
- ACM The Web Conference (WWW): 2025, 2026;
- International Conference on Learning Representations (ICLR): 2025, 2026;
- Annual AAAI Conference on Artificial Intelligence (AAAI): 2026;
- AISTATS: 2025, 2026;
- Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD): 2026;
- APWeb-WAIM Conference: 2024;
Journal Reviewer:
- Transactions on Knowledge Discovery from Data;
- Transactions on Neural Networks and Learning Systems;
- Knowledge-based Systems;
- Neural Networks;
- Neurocomputing;
- Pattern Recognition;
- Internet of Things.
📚 Teaching
Tutor
- Big Data Management (COMP9313) @ UNSW
- Database Systems (COMP9311) @ UNSW
- Machine Learning @ Nankai University
🏆 Honors & Awards
- AAAI-26 Scholarship & Volunteer Award
- University Nomination (Top 2) for Google PhD Fellowships 2025
- KDD 2025 Student Travel Award
- Development and Research Training Grant
- Google Conference Scholarship
- Outstanding Master’s Thesis Award @ Nankai University
- National Scholarship of China