About
Dr. Yang received his BEng degree in software engineering from Beijing University of Posts and Telecommunications and his PhD degree in computer science from Nanyang Technological University. Prior to joining HKBU, he was a postdoctoral research fellow at the National University of Singapore. His research focuses on developing efficient algorithms and systems for large-scale data management and analysis. His research works have been published in top-tier data management and data mining conferences/journals including SIGMOD, VLDB, TODS, KDD, WWW, etc. He received the VLDB 2021 Best Research Paper Award, the 2022 ACM SIGMOD Research Highlight Award, and the Best Paper Award Nominee in WWW 2022.
Research Interests
- Big Data Management
- Data Mining
- The Web and information retrieval
Selected Publications
- R. Yang, J. Shi, X. Xiao, Y. Yang, S. Bhowmick, and J. Liu. “PANE: Scalable and Effective Attributed Network Embedding”. In: The VLDB Journal (VLDBJ), 2023.
- Y. Li, R. Yang, J. Shi. “Efficient and Effective Attributed Hypergraph Clustering via K-Nearest Neighbor Augmentation”. In: Proceedings of the International Conference on Management of Data (SIGMOD). 2023.
- S. Zhang, R. Yang, X. Xiao, X. Yan, and B. Tang. “Effective and Efficient PageRank-based Positioning for Graph Visualization”. In: Proceedings of the International Conference on Management of Data (SIGMOD). 2023.
- R. Yang and J. Tang. “Efficient Estimation of Pairwise Effective Resistance”. In: Proceedings of the International Conference on Management of Data (SIGMOD). 2023.
- R. Yang. “Efficient and Effective Similarity Search over Bipartite Graphs”. In: The Web Conference (WWW). 2022, pp. 308–318.
- R. Yang, J. Shi, K. Huang, and X. Xiao. “Scalable and Effective Bipartite Network Embedding”. In: Proceedings of the International Conference on Management of Data (SIGMOD). 2022, pp. 1977–1991.
- R. Yang, J. Shi, X. Xiao, Y. Yang, J. Liu, and S. Bhowmick. “Scaling Attributed Network Embedding to Massive Graphs”. In: Proceedings of the VLDB Endowment (PVLDB) (2021), pp. 37–49.
- R. Yang, J. Shi, Y. Yang, K. Huang, S. Zhang, and X. Xiao. “Effective and Scalable Clustering on Massive Attributed Graphs”. In: The Web Conference (WWW). 2021, pp. 3675–3687.
- R. Yang, J. Shi, X. Xiao, Y. Yang, and S. Bhowmick. “Homogeneous Network Embedding for Massive Graphs via Reweighted Personalized PageRank”. In: Proceedings of the VLDB Endowment (PVLDB) (2020), pp. 670–683.
- J. Shi, T. Jin, R. Yang, X. Xiao, and Y. Yang. “Realtime Index-Free Single Source SimRank Processing on Web-Scale Graphs”. In: Proceedings of the VLDB Endowment (PVLDB) (2020), pp. 966–978.
- R. Yang, X. Xiao, Z. Wei, S. Bhowmick, J. Zhao, and R. Li. “Efficient Estimation of Heat Kernel PageRank for Local Clustering”. In: Proceedings of the International Conference on Management of Data (SIGMOD). 2019, pp. 1339–1356.
- S. Wang, R. Yang, X. Xiao, Z. Wei, and Y. Yang. “FORA: Simple and Effective Approximate Single-Source Personalized PageRank”. In: Proceedings of the International Conference on Knowledge Discovery and Data Mining (SIGKDD). 2017, pp. 505–514
