Sibo WANG

     Assistant Professor
     Department of Systems Engineering and Engineering Management
     The Chinese University of Hong Kong

Address: Room 507, William M. W. Mong Engineering Building, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
   Email: 
       Tel:  (852)3943-8310

Biography

I joined the Chinese University of Hong Kong (CUHK) as an Assistant Professor in Dec 2018. I received my B.E. in Software Engineering in 2011 from Fudan University and PhD in Computer Science in 2016 from Nanyang Technological University, Singapore. Before joining CUHK, I spent one and a half years at the University of Queensland, Australia as a research fellow.

Research Interest

Database and data mining, with a special interest in big data processing and analytics. Current topics include: 

• Graph data management and analysis;
• Sampling-based approximation algorithm design;
• Effective index design;
• Efficient dynamic data processing.

Hiring

I am looking for self-motivated research assistants, PhD and postdocs. For interested applicants, please send me a detailed transcript (of the applicant's undergraduate study and postgraduate study if applicable) and a CV that lists the applicant's awards (since high school) and publications.

Research Group

Current PhD and MPhil students:

• Xingguang Chen (PhD, since Fall 2019)
• Xingyi Zhang (PhD, since Fall 2019)
• Qintian Guo (PhD, since Fall 2020)
• Kun Xie (PhD, since Fall 2020)
• Xin Chen (PhD, since Fall 2020)
• Xinyu Du (PhD, since Fall 2020)
• Fangyuan Zhang (PhD, since Fall 2021)
• Xiangyu Dong (PhD, since Fall 2022)
• Guanhao Hou (MPhil, Spring 2023)

Teaching

Current teaching:

• N.A.

Past teaching:

• FTEC4005: Financial Informatics (undergraduate, 2021 Fall@CUHK)
• FTEC4003: Data Mining for FinTech (undergraduate, 2019 Fall@CUHK, 2020 Fall@CUHK, 2022 Fall@CUHK)
• CSCI2100: Data Structures (undergraduate, 2019-2023 Spring@CUHK)

Selected Publications in Recent 5 Years (A self-maintained full list. My Google Scholar / DBLP entry)

1. Xingyi Zhang, Shuliang Xu, Wenqing Lin, Sibo Wang.
   Constrained Social Community Recommendation.
   Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), to appear, 2023.
    
2. Xinyu Du, Xingyi Zhang, Sibo Wang, Zengfeng Huang.
   Efficient Tree-SVD for Subset Node Embedding over Large Dynamic Graphs.
   Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), to appear, 2023.
   paper
    
3. Guanhao Hou, Qintian Guo, Fangyuan Zhang, Sibo Wang, Zhewei Wei.
   Personalized PageRank on Evolving Graphs with an Incremental Index-Update Scheme.
   Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), to appear, 2023.
   paper
    
4. Kaixin Liu, Sibo Wang, Yong Zhang, Chunxiao Xing.
   An Efficient Algorithm for Distance-based Structural Graph Clustering.
   Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), to appear, 2023.
   paper
    
5. Fangyuan Zhang, Sibo Wang.
   Effective Indexing for Dynamic Structural Graph Clustering.
   Proceedings of the VLDB Endowment (PVLDB), 15(11): 2908-2920, 2022.
   paper
    
6. Xingguang Chen, Fangyuan Zhang, Sibo Wang.
   Efficient Approximate Algorithms for Empirical Variance with Hashed Block Sampling.
   Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 157-167, 2022.
   paper
    
7. Yanping Zheng, Hanzhi Wang, Zhewei Wei, Jiajun Liu, Sibo Wang.
   Instant Graph Neural Networks for Dynamic Graphs.
   Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 2605-2615, 2022.
    
8. Qintian Guo, Sibo Wang, Zhewei Wei, Wenqing Lin, Jing Tang.
   Influence Maximization Revisited: Efficient Sampling with Bound Tightened.
   ACM Transactions on Database Systems (TODS), 47(3): 12:1-12:45, 2022.
   paper
    
9. Xin Chen, You Peng, Sibo Wang, Jeffrey Xu Yu.
   DLCR: Efficient Indexing for Label-Constrained Reachability Queries on Large Dynamic Graphs.
   Proceedings of the VLDB Endowment (PVLDB), 15(8): 1645-1657, 2022.
   paper / code
    
10. Xingyi Zhang, Kun Xie, Sibo Wang, Zengfeng Huang. 
    Learning Based Proximity Matrix Factorization for Node Embedding.
    Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 2243-2253, 2021.
    paper / code
     
11. Hanzhi Wang, Mingguo He, Zhewei Wei, Sibo Wang, Ye Yuan, Xiaoyong Du, Ji-Rong Wen.
    Approximate Graph Propagation.
    Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 1686-1696, 2021.
    paper
     
12. Xingguang Chen, Sibo Wang.
    Efficient Approximate Algorithms for Empirical Entropy and Mutual Information.
    Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 274-286, 2021.
    paper
     
13. Guanhao Hou, Xingguang Chen, Sibo Wang, Zhewei Wei
    Massively Parallel Algorithms for Personalized PageRank.
    Proceedings of the VLDB Endowment (PVLDB), 14(9): 1668-1680, 2021.
    paper
     
14. Hanzhi Wang, Zhewei Wei, Junhao Gan, Sibo Wang, Zengfeng Huang.
    Personalized PageRank to a Targeted Node, Revisited.
    Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), pages 657-667, 2020.
    paper
     
15. Song Bian, Qintian Guo,   Sibo Wang, Jeffrey Xu Yu. 
    Efficient Algorithms for Budgeted Influence Maximization on Massive Social Networks.
    Proceedings of the VLDB Endowment (PVLDB), 13(9): 1498-1510, 2020.
    paper
     
16. Qintian Guo, Sibo Wang, Zhewei Wei, Ming Chen.
    Influence Maximization Revisited: Efficient Reverse Reachable Set Generation with Bound Tightened.
    Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 2167-2181, 2020.
    code / paper / slides
     
17. Sibo Wang, Renchi Yang, Runhui Wang, Xiaokui Xiao, Zhewei Wei, Wenqing Lin, Yin Yang, Nan Tang.
    Efficient Algorithms for Approximate Single-Source Personalized PageRank Queries.
    ACM Transactions on Database Systems (TODS), 44(4): 18:1-18:37, 2019.
    paper
     
18. Runhui Wang, Sibo Wang, Xiaofang Zhou.
    Parallelizing Approximate Single-Source Personalized PageRank Queries on Shared-Memory.
    International Journal on Very Large Data Bases (VLDBJ), 28(6):923-940, 2019.
    paper
      
19. Zhewei Wei, Xiaodong He, Xiaokui Xiao, Sibo Wang, Yu Liu, Xiaoyong Du, and Ji-Rong Wen.
    PRSim: Sublinear Time SimRank Computation on Large Power-Law Graphs.
    Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD), pages 1042-1059, 2019.
    paper
       

Services

I am/was the organizer of the following conferences/workshops:

• International Conference on Data Engineering (ICDE) 2022: Workshop Chair;

I am/was a program committee member for the following conferences/workshops:

• International Conference on Very Large Data Bases (VLDB): 2020, 2021, 2022, 2023, 2024;
• ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD): 2019, 2020, 2021, 2022, 2023;
• The Web Conference (WWW): 2020, 2021, 2022, 2023 (Best Reviewers for WWW 2023);
• International Conference on Data Engineering (ICDE): 2021, 2022, 2023;
• ACM International Conference on Web Search and Data Mining (WSDM): 2023;
• International Joint Conference on Artificial Intelligence (IJCAI): 2020, 2023;
• AAAI Conference on Artificial Intelligence (AAAI): 2021, 2022;
• SIAM International Conference on Data Mining (SDM): 2022;
• ACM International Conference on Information and Knowledge Management (CIKM): 2019, 2021, 2022, 2023;
• International Conference on Database Systems for Advanced Applications (DASFAA): 2019, 2020, 2021, 2022, 2023;
• The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD): 2018, 2019, 2020, 2021, 2022, 2023;

I am/was also the invited reviewer for the following journals:

• ACM Transactions on Database Systems (TODS),
• International Journal on Very Large Data Bases (VLDBJ),
• IEEE Transactions on Knowledge and Data Engineering (TKDE),
• ACM Transactions on Knowledge Discovery from Data (TKDD).