Kai Wang

Kai Wang

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

Kai Wang

Kai Wang is currently an associate 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.

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

Kai Wang serves as a PhD advisor, with scholarships available for master’s and PhD students. If you are interested in pursuing a Master’s or PhD degree in big data analytics, feel free to contact me!

Selected Publications and Preprints (* indicates corresponding author)

2026

  1. Aoting Zeng, Yuxin Du, Jianwei Wang, Yizhang He, Shan Jiang, Xuemin Lin, and Kai Wang. Memory as Code: Declarative Retrieval over Codified Long-Term Memory. arXiv:2610.27700, 2026.
  2. Aoting Zeng, Kai Wang, Jianwei Wang, Yuxiang Sun, Yizhang He, and Wenjie Zhang. Interpretable Unsupervised Community Detection with LLM-Symbolized Structured Processes. arXiv:2608.06402, 2026.
  3. Mo Zhou, Jianwei Wang, Kai Wang, Helen Paik, Ying Zhang, and Wenjie Zhang. Multi-Perspective Evidence Synthesis and Reasoning for Unsupervised Multimodal Entity Linking. arXiv:2604.20283, 2026.
  4. Qingshuai Feng, Shunyang Li, Kai Wang, Xuemin Lin, Kongzhang Hao, and Long Yuan. Efficient (α,β)-core Computation and On-the-fly Query at Billion Scale with GPUs. arXiv:2606.07148, 2026.
  5. Yuting Zhang, Yi Han, Kai Wang, Wei Ni, Angela Bonifati, and Wenjie Zhang. Are Large Language Models Suitable for Graph Computation? Progress and Prospects. Findings of the Association for Computational Linguistics: EMNLP 2026, pp. 23984-24001, 2026.
  6. Jiawei Zhou, Jianwei Wang*, Chenyu Zhou, Chaojian Shi, Ming Dong, and Kai Wang*. EvoSQL: Memory-Augmented Critic-Generator Co-Evolution for Text-to-SQL. Findings of the Association for Computational Linguistics: EMNLP 2026, pp. 15064-15092, 2026.
  7. Rongjie Jiang, Jianwei Wang, Gengda Zhao, Chengyang Luo, Kai Wang, and Wenjie Zhang. Advancing Multimodal Agent Reasoning with Long-Term Neuro-Symbolic Memory. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 2132-2143, 2026.
  8. Jiawei Zhou, Ruicheng Zhu, Mengshi Chen, Jianwei Wang*, and Kai Wang*. TrustResearcher: Automating Knowledge-Grounded and Transparent Research Ideation with Multi-Agent Collaboration. The ACM Web Conference 2026 (Demo), pp. 93-96, 2026.
  9. Mengshi Chen, Yuxiang Sun, Tengchao Li, Jianwei Wang*, Kai Wang, Xuemin Lin, Ying Zhang, and Wenjie Zhang. Empowering Tabular Data Preparation with Language Models: Why and How?. Annual Meeting of the Association for Computational Linguistics (ACL), pp. 228-246, 2026.
  10. Yuting Zhang, Kai Wang*, Wei Ni, Ying Zhang, and Wenjie Zhang. Agent-based Substructure Counting under Local Differential Privacy. Annual Meeting of the Association for Computational Linguistics (ACL), pp. 22518-22533, 2026.
  11. Jianwei Wang, Yuehai Wang, Kai Wang, Xuemin Lin, Wenjie Zhang, and Ying Zhang. Ensemble-based Deep Multilayer Community Search. IEEE Transactions on Knowledge and Data Engineering (TKDE), early access, 2026.
  12. Jiawei Zhou, Kai Wang*, Jianwei Wang, Kunpeng Zhang, and Xuemin Lin. COMET: An Interactive Framework for Efficient and Effective Community Search via Active Learning. INFORMS Journal on Computing (IJOC), 38(5): 1289-1306, 2026.
  13. Yihan Wu, Xuliang Zhu, Guozhong Li, Kai Wang, and Xuemin Lin. Structure-Aware Abstraction of Hierarchical Time Series. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 5500-5511, 2026.
  14. Jingye Zhao, Jianan Shen, Jianwei Wang, Tianyuan Zhou, Ruijia Wu, Kai Wang, and Xuemin Lin. Account Risk Detection in Large-Scale Financial Graphs With Auxiliary Asset Prediction. IEEE Transactions on Knowledge and Data Engineering (TKDE), 38(3): 1472-1483, 2026.
  15. Xufei Wu, Pengcheng Zhang, Yitong Song, Xiaobo Zhang, Anqi Liang, Kai Wang, Jijun Du, Yidi Xiong, Guangxu Cheng, Zhe Chen, Peng Chen, Guoliang Li, Xuanhe Zhou, and Fan Wu. TEngineDB-V: An OLAP-Native Vector Search System for Large-k Workloads at Tencent. Proceedings of the VLDB Endowment (PVLDB), 19(12): 3955-3968, 2026.
  16. Chi Luo, Jiaxin Song, Yuhao Zhang, Kai Wang, Zhixing He, and Kuan Yang. Approximate Butterfly Counting in Sublinear Time. IEEE International Conference on Data Engineering (ICDE), pp. 58-71, 2026.
  17. Haozhe Yin, Kai Wang*, Wenjie Zhang, and Xuemin Lin. Efficient Hyper-Truss Decomposition over Hypergraphs. Proceedings of the VLDB Endowment (PVLDB), 19(10): 2549-2562, 2026.
  18. Yizhang He, Wenjie Zhang, Kai Wang*, Xuemin Lin, Ying Zhang, and Wei Ni. Efficient and Effective Biclique Counting with Local Differential Privacy. Proceedings of the ACM on Management of Data (PACMMOD), 4(1): 1-24, 2026 (SIGMOD 2026).
  19. Xuliang Zhu, Xin Huang, Kai Wang, Jianliang Xu, and Xuemin Lin. From Global to Query-Dependent: Summarization of Large Hierarchical DAGs. ACM Transactions on Database Systems (TODS), 51(1), Article 6, pp. 1-31, 2026.
  20. Haozhe Yin, Kai Wang, Wenjie Zhang, Yizhang He, Ying Zhang, and Xuemin Lin. Motif Counting in Complex Networks: A Comprehensive Survey. ACM Computing Surveys (CSUR), accepted manuscript available online, 2026.
  21. Lingkai Meng, Long Yuan, Xuemin Lin, Chengjie Li, Kai Wang, and Wenjie Zhang. Counting Butterflies Over Streaming Bipartite Graphs With Duplicate Edges. IEEE Transactions on Knowledge and Data Engineering (TKDE), 38(7): 4200-4212, 2026.
  22. Lingkai Meng, Long Yuan, Xuemin Lin, Zi Chen, Shiyu Yang, and Kai Wang. DSCAN: Structural Clustering on Directed Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE), 38(10): 6511-6525, 2026.

    2025

  23. Yuren Mao, Peigen Liu, Xinjian Wang, Rui Ding, Jing Miao, Hui Zou, Mingjie Qi, Wanxiang Luo, Longbin Lai, Kai Wang, Zhengping Qian, Peilun Yang, Yunjun Gao, and Ying Zhang. Agent-Kernel: A MicroKernel Multi-Agent System Framework for Adaptive Social Simulation Powered by LLMs. arXiv:2512.01610, 2025.
  24. Jianwei Wang, Kai Wang*, Ying Zhang*, Wenjie Zhang, Xiwei Xu, and Xuemin Lin. On LLM-Enhanced Mixed-Type Data Imputation with High-Order Message Passing. Proceedings of the VLDB Endowment (PVLDB), 18(10): 3421-3434, 2025.
  25. Yitong Song, Pengcheng Zhang, Chao Gao, Bin Yao, Kai Wang, Zongyuan Wu, and Lin Qu. TRIM: Accelerating High-Dimensional Vector Similarity Search with Enhanced Triangle-Inequality-Based Pruning. Proceedings of the ACM on Management of Data (PACMMOD), 3(6): 1-26, 2025 (SIGMOD 2026).
  26. Shunyang Li, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Yizhang He. Efficient Bitruss Decomposition on GPU. IEEE Transactions on Knowledge and Data Engineering (TKDE), 37(8): 4578-4590, 2025.
  27. Jiadong Xie, Fan Zhang, Kai Wang*, Jialu Liu, Xuemin Lin, and Wenjie Zhang. Influence Minimization via Blocking Strategies. INFORMS Journal on Computing (IJOC), 37(6): 1587-1604, 2025.
  28. Yizhang He, Kai Wang*, Wenjie Zhang, Xuemin Lin, Ying Zhang, and Wei Ni. Robust Privacy-Preserving Triangle Counting under Edge Local Differential Privacy. Proceedings of the ACM on Management of Data (PACMMOD), 3(3): 1-26, 2025 (SIGMOD 2025).
  29. Jinyu Duan, Haicheng Guo, Fan Zhang, Kai Wang, Zhengping Qian, and Zhihong Tian. The k-Trine Cohesive Subgraph and Its Efficient Algorithms. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 271-282, 2025.
  30. Ruicheng Zhu#, Xintong Wang#, Kai Wang*, Fan Zhang, Zhengping Qian, and Long Yuan. Efficient k-Truss Breaking and Minimization. IEEE International Conference on Data Engineering (ICDE), pp. 2628-2641, 2025.
  31. Yuting Zhang, Wei Ni, Kai Wang*, Yizhang He, and Conggai Li. Truss Decomposition Under Edge Local Differential Privacy. IEEE International Conference on Data Engineering (ICDE), pp. 2670-2683, 2025.
  32. Gengda Zhao, Dong Wen, Xiaoyang Wang, Kai Wang, and Xuemin Lin. Preserving K-Connectivity in Dynamic Graphs. IEEE International Conference on Data Engineering (ICDE), pp. 156-169, 2025.

    2024

  33. Jianwei Wang, Kai Wang*, Xuemin Lin, Wenjie Zhang, and Ying Zhang. Efficient Unsupervised Community Search with Pre-trained Graph Transformer. Proceedings of the VLDB Endowment (PVLDB), 17(9): 2227-2240, 2024.
  34. Jianwei Wang, Ying Zhang*, Kai Wang*, Xuemin Lin, and Wenjie Zhang. Missing Data Imputation with Uncertainty-Driven Network. Proceedings of the ACM on Management of Data (PACMMOD), 2(3): 1-25, 2024 (SIGMOD 2024).
  35. Yizhang He, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Ying Zhang. Common Neighborhood Estimation over Bipartite Graphs under Local Differential Privacy. Proceedings of the ACM on Management of Data (PACMMOD), 2(6): 1-26, 2024 (SIGMOD 2025).
  36. Haozhe Yin, Kai Wang*, Wenjie Zhang, Ying Zhang, Ruijia Wu, and Xuemin Lin. Efficient Computation of Hyper-triangles on Hypergraphs. Proceedings of the VLDB Endowment (PVLDB), 18(3): 729-742, 2024 (VLDB 2025).
  37. Kai Wang, Minghao Cai, Xiaoshuang Chen, Xuemin Lin, Wenjie Zhang, Lu Qin, and Ying Zhang. Efficient algorithms for reachability and path queries on temporal bipartite graphs. The VLDB Journal (VLDBJ), 33(5): 1399-1426, 2024.
  38. Yizhang He, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Ying Zhang. Discovering Critical Vertices for Reinforcement of Large-scale Bipartite Networks. The VLDB Journal (VLDBJ), 33(6): 1861-1886, 2024.
  39. Yuwen Qian, Guodong Huang, Chuan Ma, Ming Ding, Long Yuan, Zi Chen, and Kai Wang. Enhancing Resilience in Website Fingerprinting: Novel Adversary Strategies for Noisy Traffic Environments. IEEE Transactions on Information Forensics and Security (TIFS), 19: 7216-7231, 2024.
  40. Hanchen Wang, Kai Wang, Wenjie Zhang, and Ying Zhang. Bipartite Graph Analytics: Current Techniques and Future Trends (Tutorial). IEEE International Conference on Data Engineering (ICDE), pp. 01-07, 2024.
  41. Yizhang He, Kai Wang*, Wenjie Zhang, Xuemin Lin, Wei Ni, and Ying Zhang. Butterfly Counting over Bipartite Graphs with Local Differential Privacy. IEEE International Conference on Data Engineering (ICDE), pp. 2351-2364, 2024.
  42. Shunyang Li, Kai Wang*, Xuemin Lin, Wenjie Zhang, Yizhang He, and Long Yuan. Querying Historical Cohesive Subgraphs over Temporal Bipartite Graphs. IEEE International Conference on Data Engineering (ICDE), pp. 2503-2516, 2024.
  43. Yitong Song, Kai Wang, Bin Yao, Zhida Chen, Jiong Xie, and Feifei Li. Efficient Reverse k Approximate Nearest Neighbor Search over High-Dimensional Vectors. IEEE International Conference on Data Engineering (ICDE), pp. 4262-4274, 2024.
  44. Jiujian Chen, Kai Wang, Rong-Hua Li, Hongchao Qin, Xuemin Lin, and Guoren Wang. Maximal Biclique Enumeration: A Prefix Tree Based Approach. IEEE International Conference on Data Engineering (ICDE), pp. 2544-2556, 2024.
  45. Yue Zeng, Hongchao Qin, Rong-Hua Li, Kai Wang, Guoren Wang, and Xuemin Lin. Mining Quasi-Periodic Communities in Temporal Network. IEEE International Conference on Data Engineering (ICDE), pp. 2476-2488, 2024.
  46. Siyi Teng, Jiadong Xie, Fan Zhang, Can Lu, Juntao Fang, and Kai Wang. Optimizing Network Resilience via Vertex Anchoring (Oral). ACM Web Conference (WWW), pp. 606-617, 2024.
  47. 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), pp. 320-331, 2024.

    2023

  48. Jianwei Wang, Kai Wang*, Xuemin Lin, Wenjie Zhang, and Ying Zhang. Neural Attributed Community Search at Billion Scale. Proceedings of the ACM on Management of Data (PACMMOD), 1(4): 1-25, 2023 (SIGMOD 2024).
  49. 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. Proceedings of the VLDB Endowment (PVLDB), 17(4): 657-670, 2023 (VLDB 2024).
  50. Siyi Teng, Jiadong Xie, Mingkai Zhang, Kai Wang, and Fan Zhang. IMinimize: A System for Negative Influence Minimization via Vertex Blocking. ACM International Conference on Information and Knowledge Management (CIKM), pp. 5101-5105, 2023.
  51. Yizhang He, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Ying Zhang. Scaling Up k-Clique Densest Subgraph Detection. Proceedings of the ACM on Management of Data (PACMMOD), 1(1): 1-26, 2023 (SIGMOD 2023).
  52. Fan Zhang, Qingyuan Linghu, Jiadong Xie, Kai Wang*, Xuemin Lin, and Wenjie Zhang. Quantifying Node Importance over Network Structural Stability. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 3217-3228, 2023.
  53. 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), pp. 2699-2712, 2023.
  54. 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), pp. 789-801, 2023.
  55. Kai Wang, Gengda Zhao, Wenjie Zhang, Xuemin Lin, Ying Zhang, Yizhang He, and Chunxiao Li. Cohesive Subgraph Discovery over Uncertain Bipartite Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(11): 11165-11179, 2023.
  56. 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, 2023.
  57. 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, 2023.

    2022

  58. Yuren Mao, Yaobo Liang, Nan Duan, Haobo Wang, Kai Wang, Lu Chen, and Yunjun Gao. Less-forgetting Multi-lingual Fine-tuning. Advances in Neural Information Processing Systems (NeurIPS), 35: 14917-14928, 2022.
  59. Kai Wang, Wenjie Zhang, Xuemin Lin, Lu Qin, and Alexander Zhou. Efficient Personalized Maximum Biclique Search. IEEE International Conference on Data Engineering (ICDE), pp. 498-511, 2022.
  60. 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), pp. 2291-2305, 2022.
  61. 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), pp. 2333-2345, 2022.
  62. 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), pp. 446-458, 2022.
  63. 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, 2022.
  64. Fan Zhang, Jiadong Xie, Kai Wang, Shiyu Yang, and Yu Jiang. Discovering Key Users for Defending Network Structural Stability. World Wide Web, 25(2): 679-701, 2022.
  65. Bo Tang, Man Lung Yiu, Kyriakos Mouratidis, Jiahao Zhang, and Kai Wang. On Discovering Motifs and Frequent Patterns in Spatial Trajectories with Discrete Fréchet Distance. GeoInformatica, 26(1): 29-66, 2022.
  66. 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, 2022.

    2021

  67. Yuting Zhang, Kai Wang*, Wenjie Zhang, Xuemin Lin, and Ying Zhang. Pareto-Optimal Community Search on Large Bipartite Graphs. ACM International Conference on Information and Knowledge Management (CIKM), pp. 2647-2656, 2021.
  68. Kai Wang, Yiheng Hu, Xuemin Lin, Wenjie Zhang, Lu Qin, and Ying Zhang. A Cohesive Structure Based Bipartite Graph Analytics System (Demo; CohBGA). ACM International Conference on Information and Knowledge Management (CIKM), pp. 4799-4803, 2021.
  69. Xiaoshuang Chen, Kai Wang*, Xuemin Lin, Wenjie Zhang, Lu Qin, and Ying Zhang. Efficiently Answering Reachability and Path Queries on Temporal Bipartite Graphs. Proceedings of the VLDB Endowment (PVLDB), 14(10): 1845-1858, 2021.
  70. 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), pp. 2829-2838, 2021.
  71. 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.
  72. 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), pp. 85-96, 2021.

    2016 - 2020

  73. 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), pp. 448-465, 2020.
  74. 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), pp. 661-672, 2020.
  75. Kai Wang, Xuemin Lin, Lu Qin, Wenjie Zhang, and Ying Zhang. Vertex Priority Based Butterfly Counting for Large-scale Bipartite Networks. Proceedings of the VLDB Endowment (PVLDB), 12(10): 1139-1152, 2019.
  76. 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), pp. 233-244, 2018.
  77. 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), pp. 378-389, 2017.
  78. 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), pp. 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.

Books

Academic Services

  • Organizing Committee
  • Program Committee
    • KDD 2026 (Area Chair), VLDB 2026 (Industry Track), ICDE 2026, WWW 2026, WSDM 2026.
    • KDD 2025, ICDE 2025 (Outstanding PC Member), SIGIR 2025, ICDM 2025, CIKM 2025, DASFAA 2025, APWeb-WAIM 2025.
    • VLDB 2024, KDD 2024, CIKM 2024, SDM 2024, DASFAA 2024, ECMLPKDD 2024, ASONAM 2024, ADMA 2024, APWeb-WAIM 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).
    • Intelligent Computing (Guest Editor, Special Issue on “AI Empowered Graph Computing”).
  • 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, Neural Networks, Information Sciences.

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