Welcome to the Database Group in Shenzhen University (SZU).

About the Database Group

This database group is affiliated with Big Data Institude (led by Prof. (Joshua) Zhexue Huang) in Shenzhen University. Currently, we have the following directions.

  • Efficient Algorithms for Geographic Information Systems

  • Efficient Algorithms for Large-scale Data Visualization

  • Efficient Query Processing for Spatial/Graph Databases

  • Distributed Algorithms for Spatial/Graph Databases

  • Development of Efficient Software Packages and System Prototypes

    • In this group, we have published many papers in top-tier conferences and journals in the database/data management field, including SIGMOD, PVLDB, ICDE, TODS, VLDBJ, and TKDE. If you are interested in joining us, please contact us via these two email addresses, which are (1) edisonchan2013928@gmail.com (Prof. Tsz Nam Chan) and (2) dingming.wu@gmail.com (Dr. Dingming Wu). You can click the following photos to access our personal homepages for deeply understanding our research work.
    Faculty Members

    Dr. Edison Chan
    Prof. Tsz Nam Chan
    Distinguished Professor
    BEng, PhD PolyU (HK)
    SrMIEEE, MACM
    NSF for Excellent Young Scientists (Overseas) (国家海外优青)

    		  
    Dr. Dingming Wu
    Associate Professor
    B. Sc. HUST, M. Sc. PKU,
    Ph. D. AAU (DK)

    Recruitment
    Our database group is now hiring an assistant professor and an associate researcher (副研究员). Interested applicants (1) should have strong academic background in database research or other related fields (e.g., publish papers in prestigious conferences and journals (e.g., CCF: A and CSranking)), (2) must show independent research skills and (3) must show strong presentation skills. Applicants who successfully join this research group are expected to work with us and other members in Big Data Institute.

    Major Awards
    • Tsz Nam Chan: IEEE Senior Member (Awarded in 2024)
    • Tsz Nam Chan: National Science Fund for Excellent Young Scientists (Overseas) (国家海外优青) (Awarded in 2023)
    Major Grants
    • NSFC (Excellent Young Scientists (Overseas)) 2023 "地理时空大数据分析" (Large-scale Spatiotemporal Data Analytics), 1,000,000 - 3,000,000 RMB (PI：Tsz Nam Chan) 2024 - 2027
    • NSFC (General Research Fund) 2023 "面向超大图数据分析的多样本分布式计算方法与算法研究", 500,000 RMB (PI: Dingming Wu) 2024 - 2027
    • SZU Start-up Grant 2023 "快速密度估计算法" (Fast Algorithms for Density Estimation), 300,000 RMB (PI：Tsz Nam Chan) 2024 - 2026
    • NSFC (Young Scientists Fund) 2022 "基于超快速算法的核密度估计" (Efficient Algorithms for Kernel Density Estimation), 300,000 RMB (PI：Tsz Nam Chan) 2023 - 2025
    Selected Publications
      2025
    • Siyue Wu, Dingming Wu, Junyi Quan, Tsz Nam Chan, Kezhong Lu. Efficient and Accurate PageRank Approximation on Large Graphs. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Weike Tang, Dingming Wu, Tsz Nam Chan, Kezhong Lu. Spatially Compact Dense Block Mining in Spatial Tensors. Proceedings of ACM Conference on Knowledge Discovery and Data Mining (SIGKDD).

      • 2024
    • Tsz Nam Chan, Bojian Zhu, Dingming Wu, Yun Peng, Leong Hou U. LARGE: A Length-Aggregation-based Grid Structure for Line Density Visualization. Proceedings of the VLDB Endowment (PVLDB).
    • Tsz Nam Chan, Rui Zang, Bojian Zhu, Leong Hou U, Dingming Wu, Jianliang Xu. LION: Fast and High-Resolution Network Kernel Density Visualization. Proceedings of the VLDB Endowment (PVLDB).
    • Renchi Yang, Yidu Wu, Xiaoyang Lin, Qichen Wang, Tsz Nam Chan, Jieming Shi. Effective Clustering on Large Attributed Bipartite Graphs. Proceedings of ACM Conference on Knowledge Discovery and Data Mining (SIGKDD).
    • Shunran Zhang, Xiubo Zhang, Tsz Nam Chan, Shenghui Zhang, Leong Hou U. A Computation-aware Shape Loss Function for Point Cloud Completion. Annual AAAI Conference on Artificial Intelligence (AAAI).
    • Dingming Wu, Zhaofen Zhang, Christian S. Jensen, Kezhong Lu. Efficient Skyline Keyword-Based Tree Retrieval on Attributed Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Pak Lon Ip, Shenghui Zhang, Xuekai Wei, Tsz Nam Chan, Leong Hou U. HFGNN: Efficient Graph Neural Networks using Hub-Fringe Structures. IEEE International Conference on Data Mining (ICDM).
    • Bo Guo, Zhihai Huang, Haitao Luo, Perpetual Hope Akwensi, Ruisheng Wang, Bo Huang, Tsz Nam Chan. An Enhanced Network for Extracting Tunnel Lining Defects using Transformer Encoder and Aggregate Decoder. International Journal of Applied Earth Observation and Geoinformation (IJAEOG).

      • 2023
    • Tsz Nam Chan, Leong Hou U, Byron Choi, Jianliang Xu, Reynold Cheng. Large-scale Geospatial Analytics: Problems, Challenges, and Opportunities. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Tsz Nam Chan, Rui Zang, Pak Lon Ip, Leong Hou U, Jianliang Xu. PyNKDV: An Efficient Network Kernel Density Visualization Library for Geospatial Analytic Systems. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Yun Peng, Byron Choi, Tsz Nam Chan, Jianye Yang, Jianliang Xu. Efficient Approximate Nearest Neighbor Search in Multi-dimensional Databases. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Tsz Nam Chan, Zhe Li, Leong Hou U, Reynold Cheng. PLAME: Piecewise-Linear Approximate Measure for Additive Kernel SVM. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Dingming Wu, Erjia Xiao, Yi Zhu, Christian S. Jensen, Kezhong Lu. Efficient Retrieval of the Top-k Most Relevant Event-Partner Pairs. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Xinying Lai, Dingming Wu, Christian S. Jensen, Kezhong Lu. A Re-evaluation of Deep Learning Methods for Attributed Graph Clustering. International Conference on Information and Knowledge Management (CIKM).
    • Tsz Nam Chan, Leong Hou U, Byron Choi, Jianliang Xu, Reynold Cheng. Kernel Density Visualization for Big Geospatial Data: Algorithms and Applications. IEEE International Conference on Mobile Data Management (MDM).

      • 2022
    • Tsz Nam Chan, Leong Hou U, Byron Choi, Jianliang Xu. SLAM: Efficient Sweep Line Algorithms for Kernel Density Visualization. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Tsz Nam Chan, Leong Hou U, Yun Peng, Byron Choi, Jianliang Xu. Fast Network K-function-based Spatial Analysis. Proceedings of the VLDB Endowment (PVLDB).
    • Tsz Nam Chan, Pak Lon Ip, Leong Hou U, Byron Choi, Jianliang Xu. SWS: A Complexity-Optimized Solution for Spatial-Temporal Kernel Density Visualization. Proceedings of the VLDB Endowment (PVLDB).
    • Tsz Nam Chan, Pak Lon Ip, Leong Hou U, Byron Choi, Jianliang Xu. SAFE: A Share-and-Aggregate Bandwidth Exploration Framework for Kernel Density Visualization. Proceedings of the VLDB Endowment (PVLDB).
    • Tsz Nam Chan, Pak Lon Ip, Kaiyan Zhao, Leong Hou U, Byron Choi, Jianliang Xu. LIBKDV: A Versatile Kernel Density Visualization Library for Geospatial Analytics. Proceedings of the VLDB Endowment (PVLDB).
    • Yun Peng, Byron Choi, Tsz Nam Chan, Jianliang Xu. LAN: Learning-based Approximate k-Nearest Neighbor Search in Graph Databases. IEEE International Conference on Data Engineering (ICDE).
    • Zhe Li, Man Lung Yiu, Tsz Nam Chan. PAW: Data Partitioning Meets Workload Variance. IEEE International Conference on Data Engineering (ICDE).
    • Dingming Wu, Ilkcan Keles, Song Wu, Hao Zhou, Simonas Saltenis, Christian S. Jensen, Kezhong Lu. Density-Based Top-K Spatial Textual Clusters Retrieval. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Jie Chen, Zaifeng Yang, Tsz Nam Chan, Hui Li, Junhui Hou, Lap-Pui Chau. Attention-Guided Progressive Neural Texture Fusion for High Dynamic Range Image Restoration. IEEE Transactions on Image Processing (TIP).

      • 2021
    • Tsz Nam Chan, Zhe Li, Leong Hou U, Jianliang Xu, Reynold Cheng. Fast Augmentation Algorithms for Network Kernel Density Visualization. Proceedings of the VLDB Endowment (PVLDB).
    • Tsz Nam Chan, Pak Lon Ip, Leong Hou U, Weng Hou Tong, Shivansh Mittal, Ye Li, Reynold Cheng. KDV-Explorer: A Near Real-Time Kernel Density Visualization System for Spatial Analysis. Proceedings of the VLDB Endowment (PVLDB).
    • Zhe Li, Tsz Nam Chan, Man Lung Yiu, Christian S. Jensen. PolyFit: Polynomial-based Indexing Approach for Fast Approximate Range Aggregate Queries. Proceedings of International Conference on Extending Database Technology (EDBT).
    • Zhuohao Wu, Danwen Ji, Kaiwen Yu, Xianxu Zeng, Dingming Wu, Mohammad Shidujaman. AI Creativity and the Human-AI Co-creation Model. International Conference on Human-Computer Interaction (HCI).
    • Hui Li, Tsz Nam Chan, Xianbiao Qi, Wuyuan Xie. Detail-Preserving Multi-Exposure Fusion with Edge-Preserving Structural Patch Decomposition. IEEE Transactions on Circuits and Systems for Video Technology (TCSVT).

      • 2020
    • Tsz Nam Chan, Reynold Cheng, Man Lung Yiu. QUAD: Quadratic-Bound-based Kernel Density Visualization. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Dingming Wu, Hao Zhou, Jieming Shi, Nikos Mamoulis. Top-k relevant semantic place retrieval on spatiotemporal RDF data. The VLDB Journal (VLDBJ)
    • Tsz Nam Chan, Leong Hou U, Reynold Cheng, Man Lung Yiu, Shivansh Mittal. Efficient Algorithms for Kernel Aggregation Queries. IEEE Transactions on Knowledge and Data Engineering (TKDE)
    • Zichen Zhu, Tsz Nam Chan, Reynold Cheng, Loc Do, Zhipeng Huang, Haoci Zhang. Effective and Efficient Discovery of Top-k Meta Paths in Heterogeneous Information Networks. IEEE Transactions on Knowledge and Data Engineering (TKDE)
    • Dingming Wu, Can Hou, Erjia Xiao, Christian S. Jensen. Semantic Region Retrieval from Spatial RDF Data. Database Systems for Advanced Applications (DASFAA).

      • 2019
    • Tsz Nam Chan, Man Lung Yiu, Leong Hou U. KARL: Fast Kernel Aggregation Queries. IEEE International Conference on Data Engineering (ICDE).
    • Tsz Nam Chan, Man Lung Yiu, Leong Hou U. The Power of Bounds: Answering Approximate Earth Mover's Distance with Parametric Bounds. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Dingming Wu, Dexin Luo, Christian S. Jensen, Joshua Zhexue Huang. Efficiently Mining Maximal Diverse Frequent Itemsets. Database Systems for Advanced Applications (DASFAA).
    • Dingming Wu, Yi Zhu, Christian S. Jensen. In Good Company: Efficient Retrieval of the Top-k Most Relevant Event-Partner Pairs. Database Systems for Advanced Applications (DASFAA).

      • 2018
    • Dingming Wu, Jieming Shi, Nikos Mamoulis. Density-Based Place Clustering Using Geo-Social Network Data. IEEE Transactions on Knowledge and Data Engineering (TKDE).

      • 2017
    • Hui Li, Tsz Nam Chan, Man Lung Yiu, Nikos Mamoulis. FEXIPRO: Fast and Exact Inner Product Retrieval in Recommender Systems. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Tsz Nam Chan, Man Lung Yiu, Kien A. Hua. Efficient Sub-Window Nearest Neighbor Search on Matrix. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Thanh Trinh, Dingming Wu, Joshua Zhexue Huang: A New Static Web Caching Mechanism Based on Mutual Dependency Between Result Cache and Posting List Cache. International Conference on Web Information Systems Engineering (WISE).

      • 2016
    • Jieming Shi, Dingming Wu, Nikos Mamoulis. Top-k Relevant Semantic Place Retrieval on Spatial RDF Data. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Shuyao Qi, Dingming Wu, Nikos Mamoulis. Location aware keyword query suggestion based on document proximity. IEEE International Conference on Data Engineering (ICDE).
    • Jieming Shi, Dingming Wu, Nikos Mamoulis. Textually Relevant Spatial Skylines. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Dingming Wu, Christian S. Jensen. A Density-Based Approach to the Retrieval of Top-K Spatial Textual Clusters. International Conference on Information and Knowledge Management (CIKM).

      • 2015
    • Dingming Wu, Byron Choi, Jianliang Xu, Christian S. Jensen. Authentication of Moving Top-k Spatial Keyword Queries. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Hui Li, Dingming Wu, Wenbin Tang, Nikos Mamoulis. Overlapping Community Regularization for Rating Prediction in Social Recommender Systems. ACM Conference on Recommender Systems (RecSys).
    • Tsz Nam Chan, Man Lung Yiu, Kien A. Hua. A Progressive Approach for Similarity Search on Matrix. International Symposium on Spatial and Temporal Databases (SSTD).
    • Jiafeng Hu, Reynold Cheng, Dingming Wu, Beihong Jin. Efficient Top-k Subscription Matching for Location-Aware Publish/Subscribe. International Symposium on Spatial and Temporal Databases (SSTD).

      • 2014
    • Jieming Shi, Nikos Mamoulis, Dingming Wu, David W. Cheung. Density-based Place Clustering in Geo-social Networks. Proceedings of ACM Conference on Management of Data (SIGMOD).
    • Hui Li, Dingming Wu, Nikos Mamoulis. A Revisit to Social Network-based Recommender Systems. ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
    • Yafei Li, Dingming Wu, Jianliang Xu, Byron Choi, Weifeng Su. Spatial-aware Interest Group Queries in Location-based Social Networks. Data & Knowledge Engineering (DKE)
    • Dingming Wu, Yafei Li, Byron Choi, Jianliang Xu. Social-Aware Top-k Spatial Keyword Search. IEEE International Conference on Mobile Data Management (MDM).

      • 2013
    • Lisi Chen, Gao Cong, Christian S. Jensen, Dingming Wu. Spatial Keyword Query Processing: An Experimental Evaluation. Proceedings of the VLDB Endowment (PVLDB).
    • Dingming Wu, Man Lung Yiu, Christian S. Jensen. Moving Spatial Keyword Queries: Formulation, Methods, and Analysis. ACM Transactions on Database Systems (TODS).

      • 2012
    • Xin Cao, Gao Cong, Christian S. Jensen, Jun Jie Ng, Beng Chin Ooi, Nhan-Tue Phan, Dingming Wu. SWORS: A System for the Efficient Retrieval of Relevant Spatial Web Objects. Proceedings of the VLDB Endowment (PVLDB).
    • Dingming Wu, Gao Cong, Christian S. Jensen. A Framework for Efficient Spatial Web Object Retrieval. The VLDB Journal (VLDBJ).
    • Dingming Wu, Man Lung Yiu, Gao Cong, Christian S. Jensen. Joint Top-K Spatial Keyword Query Processing. IEEE Transactions on Knowledge and Data Engineering (TKDE).
    • Yafei Li, Dingming Wu, Jianliang Xu, Byron Choi, Weifeng Su. Spatial-aware Interest Group Queries in Location-based Social Networks. International Conference on Information and Knowledge Management (CIKM).

      • 2011
    • Dingming Wu, Man Lung Yiu, Christian S. Jensen, Gao Cong. Efficient Continuously Moving Top-k Spatial Keyword Query Processing. IEEE International Conference on Data Engineering (ICDE).

      • 2009
    • Gao Cong, Christian S. Jensen, Dingming Wu. Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects. Proceedings of the VLDB Endowment (PVLDB).