Zhen Song (宋振), Associate Professor at Shandong University. I received my Bachelor’s degree in Computer Science and Technology from Northeastern University in 2017, followed by a Master’s degree in Computer Software and Theory in 2019. I then pursued my Ph.D. in Computer Science and Technology at Northeastern University under the supervision of Prof. Yu Gu (谷峪) in the research group led by Prof. Ge Yu (于戈) and obtained my doctoral degree in 2025.
From November 2022 to November 2023, I was a visiting researcher at Aalborg University, Denmark, where I worked under the supervision of Assistant Prof. Tianyi Li (李天义) in the research group of Prof. Christian S. Jensen.
Currently, I am collaborating with Prof. Lizhen Cui (崔立真) at Shandong University. My research interests include distributed computing, graph data management, and artificial intelligence training.
🔥 News
- 2025.02: 🎉🎉 We have one paper accepted by SIGMOD 2025 [CCF-A].
- 2024.06: 🎉🎉 We have one paper accepted by VLDB 2024 [CCF-A].
- 2023.08: 🎉🎉 We have one paper accepted by SIGMOD 2024 [CCF-A].
- 2021.11: 🎉🎉 We have one paper accepted by ICDE 2022 [CCF-A].
📖 Educations
- 2019.09 - 2025.01, Computer Science and Technology, Doctoral Degree, Northeastern University, Shenyang, China.
- 2022.11 - 2023.01, Computer Science , Joint Training Program, Aalborg University, Aalborg, Denmark.
- 2017.09 - 2019.06, Computer Software and Theory, Master’s Degree, Northeastern University, Shenyang, China.
- 2013.09 - 2017.06, Computer Science and Technology, Bachelor’s Degree, Northeastern University, Shenyang, China.
📝 Publications
SWASH: A Flexible Communication Framework with Sliding Window-Based Cache Sharing for Scalable DGNN Training. Zhen Song, Yu Gu, Tianyi Li, Yushuai Li, Qing Sun, Yanfeng Zhang, Christian S. Jensen, Ge Yu. SIGMOD 2025. [CCF-A].
DynaHB: A Communication-Avoiding Asynchronous Distributed Framework with Hybrid Batches for Dynamic GNN Training. Zhen Song, Yu Gu, Qing Sun, Tianyi Li, Yanfeng Zhang, Yushuai Li, Christian S. Jensen, Ge Yu. VLDB 2024. [CCF-A].
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ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling. Zhen Song, Yu Gu, Tianyi Li, Qing Sun, Yanfeng Zhang, Christian S. Jensen, Ge Yu. SIGMOD 2024. [CCF-A].
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EC-Graph: A Distributed Graph Neural Network System with Error-Compensated Compression. Zhen Song, Yu Gu, Jianzhong Qi, Zhigang Wang, Ge Yu. ICDE 2022. [CCF-A].
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DRPS: efficient disk-resident parameter servers for distributed machine learning. Zhen Song, Yu Gu, Zhigang Wang, Ge Yu. Frontiers of Computer Science (FCS) 2022. [CCF-B].
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Distributed Hypergraph Processing Using Intersection Graphs. Yu Gu, Kaiqiang Yu, Zhen Song, Jianzhong Qi, Zhigang Wang, Ge Yu, Rui Zhang. IEEE Transactions on Knowledge and Data Engineering 2022. [CCF-A].
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IncreGNN: Incremental Graph Neural Network Learning by Considering Node and Parameter Importance. Di Wei, Yu Gu, Yumeng Song, Zhen Song, Fangfang Li, Ge Yu. Dasfaa 2022. [CCF-B].
🎖 Honors and Awards
- National Scholarship for Doctoral Students, 2022