Dr. CHAN, Edison Tsz Nam
Dr. CHAN, Edison Tsz Nam

陳梓楠博士
BEng, PhD
Adjunct Assistant Professor, Department of Computer Science
https://edisonchan-szu.github.io/
 

About

Dr. Tsz Nam Chan (Edison) is currently an associate professor in the Shenzhen University (SZU). He also holds the adjunct assistant professor in 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 data engineering and data mining areas, including SIGMOD, VLDB, ICDE, and TKDE. Prior to joining the SZU, he worked as a research assistant professor in HKBU from Sep 2020 to Aug 2023 and a postdoctoral researcher 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. He also serves as the program committee members and reviewers of several prestigious conferences (e.g., VLDB (demo), ICDE, EDBT, IJCAI, DASFAA, and WISE) and journals (e.g., VLDBJ, IEEE TKDE, AIJ, IEEE TC, WWWJ, IEEE TNSE, PR Journal, DKE, JCST, The Journal of Supercomputing, Cites Journal, Remote Sensing Journal, Sensors Journal, and Entropy Journal). In addition, he is also the proceedings chair of IEEE MDM 2021 - 2024 conferences.


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

Selected 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", Proceedings of ACM Conference on Management of Data (SIGMOD), 2023 (demo track).
  • 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), 2023 (tutorial track).
  • 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).
  • 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.
  • 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), 2023 (advanced seminars track).
  • Tsz Nam Chan, Leong Hou U, Yun Peng, Byron Choi, Jianliang Xu. "Fast Network K-function-based Spatial Analysis" Proceedings of International Conference on Very Large Data Bases (PVLDB), 2022.
  • 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 International Conference on Very Large Data Bases (PVLDB), 2022 (demo track).
  • 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.
  • 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.
  • 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 International Conference on Very Large Data Bases (PVLDB), 2022.
  • 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 International Conference on Very Large Data Bases (PVLDB), 2022.
  • Zhe Li, Man Lung Yiu, Tsz Nam Chan. "PAW: Data Partitioning Meets Workload Variance", IEEE International Conference on Data Engineering (ICDE), 2022.
  • 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 International Conference on Very Large Data Bases (PVLDB), 2021 (demo track).
  • Tsz Nam Chan, Zhe Li, Leong Hou U, Jianliang Xu, Reynold Cheng. "Fast Augmentation Algorithms for Network Kernel Density Visualization", Proceedings of International Conference on Very Large Data Bases (PVLDB), 2021.
  • 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).
  • 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).
  • 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).
  • 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.
  • 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).
  • Tsz Nam Chan, Man Lung Yiu, Leong Hou U. "KARL: Fast Kernel Aggregation Queries", IEEE International Conference on Data Engineering (ICDE), 2019.
  • 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.
  • 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.