Kai Wang

Kai Wang

Assistant professor at Antai College of Economics and Management, Shanghai Jiao Tong University

Kai Wang

Kai Wang is currently an assistant professor at the Department of Data and Business Intelligence, Antai College of Economics and Management, Shanghai Jiao Tong University. Before joining SJTU, he was a Research Associate in the Data and Knowledge Research Group at University of New South Wales from 2020 to 2022. He got his Ph.D. from The University of New South Wales in 2020 and his bachelor’s degree from Zhejiang University in 2016, both in Computer Science. In 2015, He worked as a research assistant at The Hong Kong Polytechnic University.

His research interests lie in big data analytics, especially for the graph/network and spatial data. Link to Google Scholar. Email address: cskaelwang@gmail.com

I have close cooperation with many top-tier IT companies such as Alibaba DAMO Academy. For undergraduate students, please feel free to contact me via email if you are interested in big-data-related research, especially for those who want to participate in an enterprise internship or pursue a higher-level degree.

Publications (* indicates corresponding author)

  1. Jianwei Wang, Kai Wang*, Xuemin Lin, Wenjie Zhang, and Ying Zhang, Neural Attributed Community Search at Billion Scale, ACM SIGMOD International Conference on Management of Data (SIGMOD), to appear, 2024.
  2. Jianwei Wang, Ying Zhang*, Kai Wang*, Xuemin Lin, and Wenjie Zhang, Missing Data Imputation with Uncertainty-Driven Network, ACM SIGMOD International Conference on Management of Data (SIGMOD), to appear, 2024.
  3. Siyi Teng, Jiadong Xie, Fan Zhang, Can Lu, Juntao Fang, Kai Wang, Optimizing Network Resilience via Vertex Anchoring, The Web Conference (oral), to appear, 2024.
  4. Yuting Zhang, Kai Wang*, Wenjie Zhang, Wei Ni, and Xuemin Lin. Size-bounded Community Search over Large Bipartite Graphs, International Conference on Extending Database Technology (EDBT), to appear, 2024.
  5. Xinwei Cai, Xiangyu Ke, Kai Wang, Lu Chen, Tianming Zhang, Qing Liu, and Yunjun Gao. Efficient Temporal Butterfly Counting and Enumeration on Temporal Bipartite Graphs. International Conference on Very Large Data Bases (VLDB), 17(4): 657 - 670, 2023.
  6. Siyi Teng, Jiadong Xie, Mingkai Zhang, Kai Wang, and Fan Zhang. IMinimize: A System for Negative Influence Minimization via Vertex Blocking, The Conference on Information and Knowledge Management (CIKM), pages 5101–5105, 2023.
  7. Yizhang He, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Ying Zhang, Scaling Up k-Clique Densest Subgraph Detection, ACM SIGMOD International Conference on Management of Data (SIGMOD), 1(1):1-26, 2023.
  8. Fan Zhang, Qingyuan Linghu, Jiadong Xie, Kai Wang*, Xuemin Lin, Wenjie Zhang, Quantifying Node Importance over Network Structural Stability, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 3217-3228, 2023.
  9. Yiwei Zhao, Zi Chen, Long Yuan, Xuemin Lin, and Kai Wang, Index-Based Biclique Percolation Communities Search on Bipartite graphs, IEEE International Conference on Data Engineering (ICDE), pages 2699-2712, 2023.
  10. Jiadong Xie, Fan Zhang, Kai Wang, Xuemin Lin, and Wenjie Zhang, Minimizing the Influence of Misinformation via Vertex Blocking, IEEE International Conference on Data Engineering (ICDE), pages 789-801, 2023.
  11. Kai Wang, Gengda Zhao, Wenjie Zhang, Xuemin Lin, Ying Zhang, Yizhang He, Chunxiao Li. Cohesive Subgraph Discovery over Uncertain Bipartite Graphs, IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(11):11165 - 11179, 2023.
  12. Kai Wang, Xuemin Lin, Lu Qin, Wenjie Zhang, and Ying Zhang. Accelerated butterfly counting with vertex priority on bipartite graphs, The VLDB Journal (VLDBJ), 32(2): 257-281, 2022.
  13. Yixiang Fang, Kai Wang, Xuemin Lin, and Wenjie Zhang. Cohesive Subgraph Search over Big Heterogeneous Information Networks (Book), Springer Briefs in Computer Science, Springer Nature, ISBN: 978-3-030-97568-5, 2022.
  14. Yuren Mao, Yaobo Liang, Nan Duan, Haobo Wang, Kai Wang, Lu Chen, and Yunjun Gao, Less-forgetting Multi-lingual Fine-tuning, Conference on Neural Information Processing Systems (NeurIPS), pages 14917-14928, 2022.
  15. Kai Wang, Wenjie Zhang, Xuemin Lin, Lu Qin, and Alexander Zhou. Efficient Personalized Maximum Biclique Search, IEEE International Conference on Data Engineering (ICDE), pages 498-511, 2022.
  16. Kai Wang, Wenjie Zhang, Xuemin Lin, Ying Zhang, and Shunyang Li. Discovering Hierarchy of Bipartite Graphs with Cohesive Subgraphs, IEEE International Conference on Data Engineering (ICDE), pages 2291-2305, 2022.
  17. Gengda Zhao, Kai Wang*, Wenjie Zhang, Xuemin Lin, Ying Zhang, and Yizhang He. Efficient Computation of Cohesive Subgraphs in Uncertain Bipartite Graphs, IEEE International Conference on Data Engineering (ICDE), pages 2333-2345, 2022.
  18. Yizhang He, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Ying Zhang. Efficient Reinforcement of Bipartite Networks at Billion Scale, IEEE International Conference on Data Engineering (ICDE), pages 446-458, 2022.
  19. Kai Wang, Wenjie Zhang, Ying Zhang, Lu Qin, and Yuting Zhang. Discovering Significant Communities on Bipartite Graphs: An Index-based Approach, IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(3): 2471-2485, 2021.
  20. Yuting Zhang, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Ying Zhang. Pareto-Optimal Community Search on Large Bipartite Graphs, The Conference on Information and Knowledge Management (CIKM), pages 2647-2656, 2021.
  21. Kai Wang, Yiheng Hu, Xuemin Lin, Wenjie Zhang, Lu Qin, and Ying Zhang. CohBGA: A Cohesive Structure Based Bipartite Graph Analytics System (Demo), The Conference on Information and Knowledge Management (CIKM), pages 4799-4803, 2021.
  22. Xiaoshuang Chen, Kai Wang*, Xuemin Lin, Wenjie Zhang, Lu Qin, and Ying Zhang. Efficiently Answering Reachability and Path Queries on Temporal Bipartite Graphs, International Conference on Very Large Data Bases (VLDB), 14(10): 1845-1858, 2021.
  23. Yixiang Fang, Kai Wang, Xuemin Lin, and Wenjie Zhang. Cohesive Subgraph Search over Big Heterogeneous Information Networks: Applications, Challenges, and Solutions (Tutorial), ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 2829-2838, 2021.
  24. Kai Wang, Xuemin Lin, Lu Qin, Wenjie Zhang, and Ying Zhang. Towards Efficient Solutions of Bitruss Decomposition for Large-scale Bipartite Graphs, The VLDB Journal (VLDBJ), 31(2): 203-226, 2021.
  25. Yizhang He, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Ying Zhang. Exploring Cohesive Subgraphs with Vertex Engagement and Tie Strength in Bipartite Graphs, Information Sciences, 572: 277-296, 2021.
  26. Fan Zhang, Jiadong Xie, Kai Wang, Shiyu Yang, Yu Jiang. Discovering Key Users for Defending Network Structural Stability, World Wide Web, 25(2): 679-701, 2021.
  27. Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, and Kai Wang. On Discovering Motifs and Frequent Patterns in Spatial Trajectories with Discrete Frechet Distance, GeoInformatica, 26(1): 29-66, 2021.
  28. Kai Wang, Wenjie Zhang, Xuemin Lin, Ying Zhang, Lu Qin, and Yuting Zhang. Efficient and Effective Community Search on Large-scale Bipartite Graphs, IEEE International Conference on Data Engineering (ICDE), pages 85-96, 2021.
  29. Kai Wang, Shuting Wang, Xin Cao, and Lu Qin. Efficient Radius-bounded Community Search in Geo-social Networks, IEEE Transactions on Knowledge and Data Engineering (TKDE), 34(9): 4186-4200, 2020.
  30. Maryam Ghafouri, Kai Wang*, Fan Zhang, Ying Zhang, and Xuemin Lin. Efficient Graph Hierarchical Decomposition With User Engagement And Tie Strength, International Conference on Database Systems for Advanced Applications (DASFAA), pages 448-465, 2020.
  31. Kai Wang, Xuemin Lin, Lu Qin, Wenjie Zhang, and Ying Zhang. Efficient Bitruss Decomposition for Large-scale Bipartite Graphs, IEEE International Conference on Data Engineering (ICDE), pages 661-672, 2020.
  32. Kai Wang, Xuemin Lin, Lu Qin, Wenjie Zhang, and Ying Zhang. Vertex Priority Based Butterfly Counting for Large-scale Bipartite Networks, International Conference on Very Large Data Bases (VLDB), 12(10): 1139-1152, 2019.
  33. Kai Wang, Xin Cao, Xuemin Lin, Wenjie Zhang, and Lu Qin. Efficient Computing of Radius-bounded k-cores, IEEE International Conference on Data Engineering (ICDE), pages 233-244, 2018.
  34. Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, and Kai Wang. Efficient Motif Discovery in Spatial Trajectories using Discrete Fréchet Distance, International Conference on Extending Database Technology (EDBT), pages 378-389, 2017.
  35. Lu Chen, Yunjun Gao, Kai Wang, Christian S Jensen, and Gang Chen. Answering Why-not Questions on Metric Probabilistic Range Queries, IEEE International Conference on Data Engineering (ICDE), pages 767-778, 2016.

Talks

  • Cohesive Subgraph based Social Network Analysis, Fudan University, 2023.
  • Fan Zhang and Kai Wang. Cohesive Subgraph Search: Models, Algorithms, and Applications (Tutorial), APWeb-WAIM International Joint Conference on Web and Big Data (APWeb-WAIM), 2022.
  • Yixiang Fang, Kai Wang, Xuemin Lin, and Wenjie Zhang. Cohesive Subgraph Search over Big Heterogeneous Information Networks: Applications, Challenges, and Solutions (Tutorial), ACM SIGMOD International Conference on Management of Data (SIGMOD), 2021.
  • Wenjie Zhang, Kai Wang, Ying Zhang, and Xuemin Lin. Cohesive Structure based Bipartite Graph Analysis: From Motif Level to Subgraph Level (Tutorial), International Conference on Database Systems for Advanced Applications (DASFAA), 2020.
  • Towards Efficient Community Search and Reachability Query on Bipartite Graphs, Hunan University, 2021.
  • Cohesive Structure based Bipartite Network Analytics, Peking University, 2021.

Academic Services

  • Organizing Committee
  • Program Committee
    • VLDB 2024, KDD 2024, SDM 2024, DASFAA 2024, ECMLPKDD 2024, ADMA 2024, BigData 2024.
    • VLDB 2023, KDD 2023, CIKM 2023, DASFAA 2023, ECMLPKDD 2023, ADMA 2023.
    • CIKM 2022, KDD 2022 (Applied Science Track), ICDE 2022 (TKDE Poster Track), WSDM 2022, WISE 2022.
    • CIKM 2021, WISE 2021, SpatialDI 2021.
  • Editorial Board:
    • Frontiers in Big Data (Review Editor).
  • Invited Journal Reviewer
    • ACM Transaction on Database Systems (TODS), IEEE Transactions on Knowledge and Data Engineering (TKDE), The VLDB Journal (VLDBJ), INFORMS Journal on Computing (JOC), Journal of Web Semantics (JWS), World Wide Web Journal (WWWJ), Journal of Computer Science and Technology (JCST), The Journal of Supercomputing.
  • (External) Conference Reviewer
    • SIGMOD, VLDB, ICDE, KDD, WWW, EDBT, CIKM, etc.

Teaching

  • Course Instructor
    • Programming (BUSS1301) - 2023 Spring, 2024 Spring.
    • Data Structure (MGTS3401) - 2023 Autumn.
    • Data Analytics for Graphs (COMP9312) - 2021 T2 (received 100% positive ratings on teaching in the post-course survey).

Selected Awards