Full Publication List
[ # Corresponding Author, Supervising Student, Collaborating Student, * Co-first]

  1. Efficient High-Quality Clustering for Large Bipartite Graphs
    Renchi Yang, Jieming Shi#.
    SIGMOD 2024, in the Proceedings of the ACM Conference on Management of Data, 2024.

  2. Minimum Strongly Connected Subgraph Collection in Dynamic Graphs
    Xin Chen, Jieming Shi#, You Peng, Wenqing Lin, Sibo Wang, Wenjie Zhang.
    PVLDB 2024, in the Proceedings of the VLDB Endowment, 2024.

  3. BOURNE: Bootstrapped Self-supervised Learning Framework for Unified Graph Anomaly Detection
    Jie Liu, Mengting He, Xuequn Shang, Jieming Shi, Bin Cui, Hongzhi Yin
    ICDE 2024, in the Proceedings of the IEEE International Conference on Data Engineering, 2024.

  4. Low Latency and Sparse Computing Spiking Neural Networks With Self-Driven Adaptive Threshold Plasticity.
    Anguo Zhang, Jieming Shi, Junyi Wu, Yongcheng Zhou, Wei Yu.
    TNNLS 2023, IEEE Transactions on Neural Networks and Learning Systems, 2023.

  5. LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings.
    Ningyi Liao, Siqiang Luo, Xiang Li, Jieming Shi.
    NeurIPS 2023, in the Proceedings of the Advances in Neural Information Processing Systems, 2023.

  6. Anomaly Detection in Financial Transactions Via Graph-Based Feature Aggregations.
    Hewen Wang, Renchi Yang, Jieming Shi.
    International Conference on Big Data Analytics and Knowledge Discovery, 2023.

  7. Effective and Efficient Route Planning Using Historical Trajectories on Road Networks
    Tian Wei, Jieming Shi, Siqiang Luo, Hui Li, Xike Xie, Yuanhang Zou.
    PVLDB 2023, in the Proceedings of the VLDB Endowment, 2023.

  8. EmbedX: A Versatile, Efficient and Scalable Platform to Embed Both Graphs and High-Dimensional Sparse Data
    Yuanhang Zou*, Zhihao Ding*, Jieming Shi, Shuting Guo, Chunchen Su, Yafei Zhang.
    PVLDB 2023, in the Proceedings of the VLDB Endowment, 2023.

  9. SlotGAT: Slot-based Message Passing for Heterogeneous Graphs.
    Ziang Zhou, Jieming Shi, Renchi Yang, Yuanhang Zou, Qing Li
    ICML 2023, International Conference on Machine Learning, 2023.

  10. Efficient and Effective Attributed Hypergraph Clustering via K-Nearest Neighbor Augmentation.
    Yiran Li, Renchi Yang, Jieming Shi
    SIGMOD 2023, in the Proceedings of the ACM Conference on Management of Data, 2023.

  11. PANE: Scalable and Effective Attributed Network Embedding
    Renchi Yang, Jieming Shi, Xiaokui Xiao, Yin Yang, Sourav S. Bhowmick, Juncheng Liu
    VLDB Journal, 2023.

  12. Effective Stabilized Self-Training on Few-Labeled Graph Data.
    Ziang Zhou, Jieming Shi, Shengzhong Zhang, Zengfeng Huang, Qing Li
    Information Sciences (JCR Q1), 2023.

  13. Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning.
    Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, S.M. Yiu, Yiding Liu, Gao Cong, Jieming Shi
    ICDE 2023, in the Proceedings of the IEEE International Conference on Data Engineering, 2023.

  14. Efficiently Answering k-hop Reachability Queries in Large Dynamic Graphs for Fraud Feature Extraction.
    Zequan Xu, Siqiang Luo, Jieming Shi, Hui Li, Chen Lin, Qihang Sun, Shaofeng Hu
    MDM 2022 , in the Proceedings of the IEEE International Conference on Mobile Data Management, 2022.

  15. No PANE, No Gain: Scaling Attributed Network Embedding in a Single Server. (SIGMOD Research Highlights Award)
    Renchi Yang, Jieming Shi, Xiaokui Xiao, Yin Yang, Sourav S Bhowmick, Juncheng Liu
    ACM SIGMOD Record, 2022.

  16. Scalable and Effective Bipartite Network Embedding.
    Renchi Yang, Jieming Shi, Keke Huang, Xiaokui Xiao
    SIGMOD 2022, in the Proceedings of the ACM Conference on Management of Data, 2022.

  17. Example-based Spatial Search at Scale.
    Hanyuan Zhang, Siqiang Luo, Jieming Shi, Jing Nathan Yan, Weiwei Sun
    ICDE 2022, in IEEE International Conference on Data Engineering, 2022.

  18. MOTS: Minimax Optimal Thompson Sampling.
    Tianyuan Jin, Pan Xu, Jieming Shi, Xiaokui Xiao, and Quanquan Gu
    ICML 2021, in the Proceedings of the International Conference on Machine Learning, 2021.

  19. Unconstrained Submodular Maximization with Modular Costs: Tight Approximation and Application to Profit Maximization.
    Tianyuan Jin, Yu Yang, Renchi Yang, Jieming Shi#, Keke Huang, and Xiaokui Xiao.
    PVLDB 2021, in the Proceedings of the VLDB Endowment, 14(10):1756-768, 2021.

  20. "Effective and Scalable Clustering on Massive Attributed Graphs".
    Renchi Yang, Jieming Shi#, Yin Yang, Keke Huang, Shiqi Zhang and Xiaokui Xiao
    TheWebConf (WWW) 2021, in the Proceedings of The Web Conference, 2021.

  21. "Scaling Attributed Network Embedding to Massive Graphs".
    Renchi Yang, Jieming Shi, Xiaokui Xiao, Yin Yang, Juncheng Liu, Sourav S Bhowmick.
    PVLDB 2021, in the Proceedings of the VLDB Endowment, 2021.

  22. "Top-k Closest Pair Queries over Spatial Knowledge Graph".
    Fangwei Wu, Xike Xie, Jieming Shi.
    DASFAA 2021, International Conference on Database Systems for Advanced Applications, 2021.

  23. "Multi-task Learning for Recommendation over Heterogeneous Information Network".
    Hui Li, Yanlin Wang, Ziyu Lyu, Jieming Shi.
    TKDE 2020, IEEE Transactions on Knowledge and Data Engineering, 2020.

  24. "Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs".
    Jieming Shi*, Tianyuan Jin*, Renchi Yang, Xiaokui Xiao, Yin Yang. [Code]
    PVLDB 2020, in the Proceedings of the VLDB Endowment, 2020.

  25. "Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank".
    Renchi Yang, Jieming Shi, Xiaokui Xiao, Yin Yang, Sourav S Bhowmick.
    PVLDB 2020, in the Proceedings of the VLDB Endowment, 2020.

  26. "Realtime Top-k Personalized PageRank over Large Graphs on GPUs". [Technical Report]
    Jieming Shi, Renchi Yang, Tianyuan Jin, Xiaokui Xiao, Yin Yang. [Code]
    PVLDB 2020, in the Proceedings of the VLDB Endowment, 2020.

  27. "Efficient Pure Exploration in Adaptive Round model".
    Tianyuan Jin, Jieming Shi, Xiaokui Xiao, Enhong Chen.
    NeurIPS 2019, in the Proceedings of the Advances in Neural Information Processing Systems, 2019.

  28. "Top-k Relevant Semantic Place Retrieval on Spatio-temporal RDF Data".
    Dingming Wu, Hao Zhou, Jieming Shi#, Nikos Mamoulis.
    VLDBJ 2019, International Journal on Very Large Data Bases, 2019.

  29. "Density-based Place Clustering Using Geo-Social Network Data".
    Dingming Wu, Jieming Shi#, Nikos Mamoulis.
    TKDE 2018, IEEE Transactions on Knowledge and Data Engineering, 2018.

  30. "Top-k Relevant Semantic Place Retrieval on Spatial RDF Data".
    Jieming Shi, Dingming Wu, Nikos Mamoulis.
    SIGMOD 2016, in the Proceedings of the ACM Conference on Management of Data, San Francisco, CA, June 2016.

  31. "Textually Relevant Spatial Skylines".
    Jieming Shi, Dingming Wu, Nikos Mamoulis.
    TKDE 2016, IEEE Transactions on Knowledge and Data Engineering, 2016.

  32. "Density-based Place Clustering in Geo-Social Networks".
    Jieming Shi, Nikos Mamoulis, Dingming Wu, David W. Cheung.
    SIGMOD 2014, in the Proceedings of the ACM Conference on Management of Data, Snowbird, UT, June 2014.

  33. "Clustering in Geo-Social Networks".
    Dingming Wu, Nikos Mamoulis, Jieming Shi.
    IEEE Data Engineering Bulletin, 38(2): 47-57, 2015.