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Kaixin Wang（王恺忻）


Assistant Professor
> College of Computer Science, Beijing University of Technology (BJUT)

Email: kaixin.wang@bjut.edu.cn (may also contact via kaixin001@e.ntu.edu.sg)
Office: 815, Software Building, BJUT

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Biography

Currently, Dr. Kaixin Wang is an Assistant Professor at School of Computer Science and Engineering, Beijing University of Technology, Beijing, China. Prior to that, he received his PhD degree from College of Computing and Data Science (School of Computer Science and Engineering till April 2024) of Nanyang Technological University (NTU) in 2024. He received his bachelor's degree from Beihang University in 2019.

His general research interest lies in graph data mining and management, particularly subgraph counting and enumeration, cohesive subgraph mining and graph algorithms. Till now, he has published several papers in the areas of database and data mining, and most of them were in top-tier conferences and journals (e.g., SIGMOD, TKDE).

Publications (* indicates Kaixin as a corresponding author)

Conference Papers

  1. Kaixin Wang, Kaiqiang Yu, Cheng Long, "Efficient k-Clique Listing: An Edge-Oriented Branching Strategy", in Proceedings of ACM International Conference on Management of Data (SIGMOD'24). [Proc.] [Technical Report] [Code]

  2. Kaixin Wang, Cheng Long, Da Yan, Jie Zhang, H. V. Jagadish, "Reinforcement Learning Enhanced Weighted Sampling for Accurate Subgraph Counting on Fully Dynamic Graph Streams", in Proceedings of the 39th International Conference on Data Engineering (ICDE'23). [Proc.] [Technical Report] [Code]

  3. Kaixin Wang, Cheng Long, Yongxin Tong, Jie Zhang, Yi Xu, "Adaptive Holding for Online Bottleneck Matching with Delays", in Proceedings of the 2021 SIAM International Conference on Data Mining (SDM'21). [Proc.] [Technical Report] [Code]

Journal Papers

  1. Kaixin Wang, Cheng Long, Darrell Joshua Ong, Jie Zhang and Xue-Ming Yuan, "Single-site Perishable Inventory Management under Uncertainties: A Deep Reinforcement Learning Approach", in IEEE Transactions on Knowledge and Data Engineering (TKDE'23). [Journal] [Technical Report] [Code]

Selected Awards

Research Service

External Reviewer

Journal Reviewer: TKDE

Teaching Assistant