Homepage of Chan Tsz Nam

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"

Biography

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.

Recruitment

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

Complexity-Optimized Algorithms for Large-scale Kernel Density Visualization (April 2023), Nanyang Technological University (Singapore)
Complexity-Optimized Algorithms for Large-scale Kernel Density Visualization (December 2022), Shandong University (China)
A Complexity-Optimized Solution for Large-scale Kernel Density Visualization (December 2022), Shenzhen University (China)

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

Tutorials

Tsz Nam Chan, Leong Hou U, Byron Choi, Jianliang Xu, Reynold Cheng.
Large-scale Geospatial Analytics: Problems, Challenges, and Opportunities (1.5 hours)
Proceedings of ACM Conference on Management of Data (SIGMOD), 2023. (Short Video)

Tsz Nam Chan, Leong Hou U, Byron Choi, Jianliang Xu, Reynold Cheng.
Kernel Density Visualization for Big Geospatial Data: Algorithms and Applications (1.5 hours)
IEEE International Conference on Mobile Data Management (MDM), 2023.

Software Development/Demo Publications

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 (Library Homepage)
Proceedings of ACM Conference on Management of Data (SIGMOD), 2023. (Short Video)

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 (Library Homepage)
Proceedings of the VLDB Endowment (PVLDB), 2022. (Video Presentation)
Impact case 1: Used in the Macau COVID-19 HotSpot Map (Project Website) (News) (Video News (in Cantonese))
Impact case 2: Used in the Hong Kong COVID-19 HotSpot Map (Project Website) (News) (News (in Chinese))

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 (Project Homepage)
Proceedings of the VLDB Endowment (PVLDB), 2021. (Video Presentation)

Research Publications [DBLP][Google Scholar]

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). (Code)

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), 2023. (Code) (Short Video)
Appear in the new ACM journal "Proceedings of the ACM on Management of Data (PACMMOD)".

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), 2022. (Code)
(Video Presentation) (Powerpoint Presentation) (Technical Report) (Poster Presentation)

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).

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), 2022. (Code)

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), 2022. (Code)
(Video Presentation) (Powerpoint Presentation)

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), 2022. (Code)
(Video Presentation) (Powerpoint Presentation) (Technical Report) (Poster Presentation)

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), 2022. (Code)
(Video Presentation) (Powerpoint Presentation) (Poster Presentation)

Zhe Li, Man Lung Yiu, Tsz Nam Chan.
PAW: Data Partitioning Meets Workload Variance
IEEE International Conference on Data Engineering (ICDE), 2022. (Simulation Code) (Spark Code)

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), 2021. (Code)
(Video Presentation) (Powerpoint Presentation) (Remark)

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), 2021.

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). (Code)

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). (Code)

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). (Code)

Tsz Nam Chan, Reynold Cheng, Man Lung Yiu.
QUAD: Quadratic-Bound-based Kernel Density Visualization
Proceedings of ACM Conference on Management of Data (SIGMOD), 2020. (Code)
(Video Presentation) (Powerpoint Presentation) (Technical Report)

Tsz Nam Chan.
Similarity Measures: Algorithms and Applications
PhD Thesis.

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). (Code)
Extended abstract in IEEE International Conference on Data Engineering (ICDE), 2020. (Video Presentation)

Tsz Nam Chan, Man Lung Yiu, Leong Hou U.
KARL: Fast Kernel Aggregation Queries
IEEE International Conference on Data Engineering (ICDE), 2019. (Code) (Poster Presentation)

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).

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), 2017. (Code)

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), 2015.

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

Teaching

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).