Dr. Tsz Nam Chan (Edison)

Research Assistant Professor

Department of Computer Science
Hong Kong Baptist University
Office: DLB804
my email: edisonchan@comp.hkbu.edu.hk
Remember: "Try our best and prepare for the worst"


Tsz Nam Chan (Edison) is currently a Research Assistant Professor in the database group of the Hong Kong Baptist University (HKBU). He is a data engineering researcher (for handling the efficiency issues in big data settings). He published several research papers in prestigious conferences and journals (CCF: A, top ranking in Google scholar and Microsoft) in both database (data engineering) and data mining areas, including SIGMOD, VLDB, ICDE, and TKDE. Prior to joining the HKBU, he worked as the postdoctoral researcher (with Prof. Reynold Cheng) in The University of Hong Kong (HKU) from Sep 2018 to Aug 2020. He received the PhD degree in computing and the BEng degree in electronic and information engineering from The Hong Kong Polytechnic University in 2019 and 2014, respectively. His PhD supervisor is Dr. Man Lung Yiu (Ken). He is an IEEE member and an ACM member.


Tsz Nam Chan can recruit multiple postdoctoral researchers, postgraduate students, and software developers starting from September 2023. If you are interested in developing efficient software packages/systems (like LIBKDV and KDV-Explorer) or complexity-reduced algorithms (like SLAM, SWS, SAFE, and PLAME) that are related to spatial/multi-dimensional databases, GIS, and statistical models, please contact me.

Research Interests

  • Algorithm and software development for statistical models (with non-trivial accuracy and time complexity guarantees)

  • Spatial and temporal data analysis/management (develop efficient algorithms for GIS)

  • Large-scale data visualization

  • Kernel methods, similarity measures, similarity search, and pattern matching

  • Long-term Goal

    My long-term goal aims to develop the GIS (or spatial analysis), visualization, statistical, and machine learning software packages, like QGIS, ArcGIS, CrimeStat, Seaborn, Scikit-learn, Scipy, and LIBSVM, which are based on our theoretically efficient algorithms (e.g., reduce the time complexity) with non-trivial accuracy guarantees (e.g., achieve exact results or approximate results with approximation ratio). With the lower time complexity of our solutions, our software packages should be the fastest in the world.

    Academic Talks
    Research Grants
    • PI: NSFC 2022 "基于超快速算法的核密度估计" (Efficient Algorithms for Kernel Density Estimation), 300,000 RMB
    • PI: HKBU Internal Grant, 100,000 HKD
    • PI: HKBU Start-up Grant, 120,000 HKD
    Software Development/Demo Publications
    Research Publications [DBLP][Google Scholar]
    Professional Services
    • Journal Referee
      • The International Journal on Very Large Data Bases (VLDBJ)
      • IEEE Transactions on Knowledge and Data Engineering (TKDE)
      • IEEE Transactions on Computers (TC)
      • World Wide Web Journal (WWWJ)
      • IEEE Transactions on Network Science and Engineering (TNSE)
      • Pattern Recognition (PR)
      • Data and Knowledge Engineering (DKE)
      • The Journal of Supercomputing
      • Cities Journal
      • Remote Sensing Journal
      • Sensors Journal
      • Entropy Journal
    • Conference Program Organizer
      • International Conference on Mobile Data Management (MDM) Year: 2021, 2022, 2023 proceedings chair
    • Conference Program Committee/Reviewer
      • International Conference on Very Large Data Bases (VLDB) Year: 2022 (demo track), 2023 (demo track)
      • IEEE International Conference on Data Engineering (ICDE) Year: 2022
      • Proceedings of International Conference on Extending Database Technology (EDBT) Year: 2023
      • International Joint Conference on Artificial Intelligence (IJCAI) Year: 2020
      • International Conference on Database Systems for Advanced Applications (DASFAA) Year: 2021, 2022, 2023
      • International Conference on Web Information Systems Engineering (WISE) Year: 2019, 2020, 2021, 2022, 2023
    • Conference Program Session Chair
      • International Conference on Very Large Data Bases (VLDB) Year: 2020, 2022
      • IEEE International Conference on Data Engineering (ICDE) Year: 2021
      • International Joint Conference on Web and Big Data (APWeb-WAIM) Year: 2021
      • International Conference on Web Information Systems Engineering (WISE) Year: 2021
    • Conference Program External Reviewer
      • Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD) Year: 2019, 2020
      • Proceedings of ACM Conference on Management of Data (SIGMOD) Year: 2022
      • International Conference on Very Large Data Bases (VLDB) Year: 2020, 2021
      • IEEE International Conference on Data Engineering (ICDE) Year: 2021
    • HKBU COMP 7640 Database Systems and Administration (Spring 2023)
    • HKBU COMP 7930 Big Data Analytics (Spring 2021, Spring 2022)
    • HKBU COMP 4035 Database System Implementation (Fall 2020, Fall 2021, Fall 2022)
    How to be Productive in Research?

    If you want to be productive in research, you need to read this document (by Prof. Dimitris Papadias in HKUST), read this Zhihu blog (written in Chinese), and watch this video (by Prof. Baochun Li in the University of Toronto).