Zezhong Ding (丁泽中)

My heart is in the data research!

✉️ Email: zezhongding AT mail DOT ustc DOT edu DOT cn
🏫 University of Science and Technology of China (USTC)

Google Scholar, Github

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Zezhong is a Ph.D. candidate (successive master-doctor program since 2022) in Data Darkness Lab (DDL), School of Artificial Intelligence and Data Science, University of Science and Technology of China (USTC), supervised by Prof. Xike Xie. He was a research assistant at Department of Computer Science, Hong Kong Baptist University, from Nov. 2024 to Feb. 2025, working with Prof. Jianliang Xu. He received his B.Eng. (Hons) degree in Computer Science and Technology from Ocean University of China in 2022. He has published several research papers in prestigious conferences such as ACM SIGMOD. His general research interests mainly focus on the data management algorithms and machine learning systems over big data, particularly big graph data.

📌 Welcome to contact me for any discussion!😊

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Research Interests

• Data Management Algorithms
• 🎯Distributed Computing: How to Partition Big Data for Distributed Computing?
  • [S5P, SIGMOD-24]: Streaming Skewness-aware Graph Partitioner
  • [ClusPar, TC-25]: Streaming Game-Theoretic Graph Partitioner (Journal Extension of [CLUGP, ICDE-22])
• 🎯Large Language Models (LLMs): How to Manage Big Graph Data for Enhancing LLMs' ability to understand graphs?
  • [GraphInsight, ACL-25]: LLM (w/ RAG) for Graph Structure Understanding
• 🎯Graph Foundation Models (GFMs): How to Design Scalable and Efficient GFMs to enhance the Performance and Capabilities of Graph-Related Applications?
• Machine Learning Systems
• 🎯Out-of-Core Graph Machine Learining Systems: How to Overcome Memory Bound Challenges for Big Graph Data?
  • [Capsule, SIGMOD-25]: Out-of-Core Graph Training Mechanism
  • [SWIFT, SIGMOD-26]: Enabling Large-Scale Temporal Graph Learning on a Single Machine

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News

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Selected Publications

You can find the full list of my publications here, my DBLP entry here and my Google Scholar entry here.

Remark: ¹ indicates co-first authors, * indicates corresponding author

• 📄[SIGMOD-26] Rui Guo¹, Zezhong Ding¹, Xike Xie^*, Jianliang Xu, SWIFT: Enabling Large-Scale Temporal Graph Learning on a Single Machine, Proceedings of the ACM on Management of Data, 2026. (PDF)(Source Code)
• 📄[SIGMOD-25] Yongan Xiang¹, Zezhong Ding¹, Rui Guo, Shangyou Wang, Xike Xie^*, S. Kevin Zhou, Capsule: an Out-of-Core Training Mechanism for Colossal GNNs, Proceedings of the ACM on Management of Data 3 (1), 2025. (PDF)(Source Code)(Source Code)(Slides)(Press Release)
• 📄[TC-25] Zezhong Ding¹, Deyu Kong¹, Zhuoxu Zhang, Xike Xie^*, Jianliang Xu, ClusPar: A Game-Theoretic Approach for Efficient and Scalable Streaming Edge Partitioning, IEEE Transactions on Computers 74 (1), 2025. (PDF)(Source Code)
• 📄[SIGMOD-24] Zezhong Ding, Yongan Xiang, Shangyou Wang, Xike Xie^*, S. Kevin Zhou, Play like a Vertex: A Stackelberg Game Approach for Streaming Graph Partitioning, Proceedings of the ACM on Management of Data 2 (3), 2024. (PDF)(Source Code)(Slides)(Press Release)

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Selected Awards

• National Scholarship (China) (three times, in 2019, 2021, and 2024)
• Gold Medal in International Genetically Engineered Machine Competition (2021)
• Finalist (Nomination for Grand Prize) in MCM (USA) (Top 1%, 2021)

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Academic Services

I am/was a program committee member/reviewer for the following conferences/journals:

• SIGMOD 2025 (ARI), TKDD 2024, NeurIPS 2024,ICDE 2024|2025,SIGIR 2022

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Hobbies

Basketball🏀, Soccer ⚽️, Moive 🎬, Singing 🎤, Games 🎮, Snooker 🎱, Swimming 🏊

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Love: Ariel@Amsterdam

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