Yixiang Fang

Associate Professor
School of Data Science, The Chinese University of Hong Kong, Shenzhen
Longgang District, Shenzhen City, Guangdong Province, China

Coach of CUHK-Shenzhen Programming Contest Team

Email: fangyixiang at cuhk.edu.cn

[Google Scholar], [DBLP]

Recent News

  • [2025-7] Yixiang received the 2025 CUHK-Shenzhen Excellent Teaching Achievement Award.
  • [2025-4] Call for paper: LLM+Graph@VLDB2025 Workshop
  • [2025-3] We have conducted an in-depth study of graph-based Retrieval-Augmented Generation (RAG) and released a paper at https://www.arxiv.org/abs/2503.04338. We have implemented more than 10 graph-based methods under a unified framework, where the codes are available at https://github.com/JayLZhou/GraphRAG in Github.
  • [2025-1] Yixiang is looking for highly self-motivated PostDocs, PhD/MPhil students, and RAs to work on the topic of LLM+Graph. Please see the [Recruitment Details] and contact him if you are interested.
  • [2024-9] Yixiang is teaching CSC3100 Data Structures for undergraduate students and CSC6001 Analysis of Algorithms for graduate students in Fall 2024 semester.

Biography

Yixiang Fang is an Associate Professor in the School of Data Science at the Chinese University of Hong Kong, Shenzhen. Previously, he was a Research Associate in the School of Computer Science and Engineering, the University of New South Wales (UNSW), working with Prof. Xuemin Lin. He received the PhD from Department of Computer Science in the University of Hong Kong (HKU) in 2017, advised by Prof. Reynold Cheng. He was a visiting scholar at Nanyang Technological University in 2016, working with Prof. Gao Cong.

Yixiang Fang's general research interests mainly focus on the data management, data mining, and artificial intelligence over big data, particularly big graph data. He has published extensively in the areas of database and data mining, including One of the Best Papers in SIGMOD 2020 (a world flagship conference in database areas), and most of them are published in top-tier conferences (e.g., PVLDB, SIGMOD, ICDE, NeurIPS, WWW, AAAI, and IJCAI) and journals (e.g., TODS, VLDBJ, and TKDE). He was awarded the 2021 ACM SIGMOD Research Highlight Award and 2025 CUHK-Shenzhen Excellent Teaching Achievement Award. Currently, he is an editorial board member of the journal Information Processing & Management (IPM, IF: 6.9). He was a PC co-chair of LLM+Graph@VLDB2025 workshop. He has also served on the program committees for several top conferences (e.g., VLDB, ICDE, KDD, AAAI, and IJCAI) and as invited reviewers for top journals (e.g., TKDE and VLDBJ) in the areas of database, data mining, and artificial intelligence. He is a member of ACM, IEEE, and CCF.

Recent Research Interests

Yixiang Fang's general research interests mainly focus on the data management, data mining, and artificial intelligence over big data, particularly big graph data. Currently, he is mainly working on the research topics of densest subgraph discovery, community search, path/connectivity computation, LLM + Graph (e.g., graph-based retrieval augmented generation), and so on.

Contact

Office address:
Room 521a, Dao Yuan Building, CUHK-Shenzhen
2001 Longxiang Road, Longgang District, Shenzhen, China
Email: fangyixiang at cuhk.edu.cn
          fangyixianghku at gmail.com (preferred)
Telephone: +86-755-23517019

Research Interests: Overview

Yixiang Fang's general research interests mainly focus on the data management, data mining, and artificial intelligence over big data, particularly big graph data. Currently, he is working on the following research topics:

The two most representative topics that Yixiang has studied are Community Search and Densest Subgraph Discovery, which are introduced as follows.

Representative Research Topics

Topic 1: Community Search (CS)

As a hot research topic in the network science, community search (CS) aims to efficiently find the most likely community that contains the query vertex. It has attracted great attention from both academic and industry areas, and found various real-world applications, such as friend recommendation, event organization, fraud detection, network analysis, and retrieval augmented generation (RAG) for LLMs. Yixiang has systematically studied this topic and made many contributions, including

  • CS on attributed graphs: VLDB'2016, VLDB'2017, VLDBJ'2017, TKDE'2019.
  • CS on directed graphs: TKDE'2019, IJCAI'2020, VLDB'2024.
  • CS on heterogeneous graphs: VLDB'2020, VLDB'2022, VLDB'2023, ICDE'2024, VLDB'2025.
  • A demo system (called C-Explorer): VLDB'2017
  • CS tutorial and survey: SIGMOD'2021, VLDBJ'2020
  • A book entitled Cohesive Subgraph Search over Big Heterogeneous Information Networks

In particular, Yixiang's works on cohesive subgraphs have been well recognized by leading IT companies. His works on community search on knowledge graphs and temporal graphs have been funded by CCF-Huawei Populus euphratica Fund and ByteDance, respectively.
Recently, Yixiang has been focusing on the Retrieval-Augmented Generation (RAG) for LLMs via CS solutions, supported by Huawei Cloud. Note that since it also queries subgraphs from knowledge graphs, it can be considered as a continuation of Yixiang's prior research on CS. He has proposed a novel graph-based RAG approach (arXiv'2025) and performed an in-depth study of graph-based RAG approaches (arXiv'2025).

DSD example
Figure 1: C-Explorer.

Award
Figure 2: A book of CS.

Topic 2: Densest Subgraph Discovery (DSD)

As one of the most fundamental problems in graph mining, DSD aims to discover the subgraph with the highest density from a given graph. This topic has garnered tremendous attention from both database and theory areas in recent years. It has found a broad spectrum of real applications, such as network community detection, graph index construction, regulatory motif discovery in DNA, fake follower detection, etc. Yixiang has continuously worked on this topic, and innovatively addressed this problem by developing a k-core-based paradigm. He has achieved a series of breakthroughs on this research topic, including

  • Algorithms for DSD on undirected graphs: VLDB'2019, ICDE'2023, SIGMOD'2024, VLDB'2025
  • Algorithms for DSD on directed graphs: SIGMOD'2020, TODS'2021, SIGMOD Record'2021, SIGMOD'2022, VLDBJ'2024
  • A generalized graph density metric: SIGMOD'2023, VLDBJ'2024
  • Parallel DSD algorithms: ICDE'2023
  • An in-depth experimental study of existing DSD solutions: VLDB'2025
  • DSD tutorial and survey: VLDB'2022, arXiv'2024

In particular, Yixiang's SIGMOD'2020 paper was selected as One of the four Best Papers in SIGMOD'2020 conference, and his paper, entitled Efficient Directed Densest Subgraph Discovery, was awarded The 2021 SIGMOD Research Highlight Award, which aims to showcase a set of research projects that exemplify core database research, address an important problem, represent a definitive milestone in solving the problem, and have the potential of significant impact.

DSD example
Figure 3: An example of DSD.

Award
Figure 4: An in-depth study of existing DSD algorithms.

In addition, Yixiang has also made some important contributions on the topics of connectivity/path queries, motif counting, node importance estimation, similarity/relevance computation, graph clustering, and so on.

Research Honors

Selected Publications

[ Full List, Google Scholar, DBLP, * indicates that Yixiang is a corresponding author ]
  1. Yuyang Xia, Yixiang Fang*, Wensheng Luo. Efficiently Counting Triangles in Large Temporal Graphs. ACM International Conference on Management of Data (SIGMOD), 3(1):38:1-38:27, 2025.
  2. Yuanyuan Zeng, Yixiang Fang*, Wensheng Luo, Chenhao Ma. Accelerating Skyline Path Enumeration with a Core Attribute Index on Multi-attribute Graphs. ACM International Conference on Management of Data (SIGMOD), 3(3):124:1-124:1:26, 2025.
  3. Shu Wang, Yixiang Fang*, Wensheng Luo. Searching and Detecting Structurally Similar Communities in Large Heterogeneous Information Networks. Proceedings of the VLDB Endowment (PVLDB), 18(5): 1425-1438, 2025.
  4. Yingli Zhou, Qingshuo Guo, Yixiang Fang*. Efficient k-Clique Densest Subgraph Discovery: Towards Bridging Practice and Theory. Proceedings of the VLDB Endowment (PVLDB), 18(10): 3490-3503, 2025.
  5. Yufan Sheng, Xin Cao, Kaiqi Zhao, Yixiang Fang, Jianzhong Qi, Wenjie Zhang, Christian S. Jensen. ACE: A Cardinality Estimator for Set-Valued Queries. Proceedings of the VLDB Endowment (PVLDB), 18(7): 2112-2125, 2025.
  6. Yuanyuan Zeng, Yixiang Fang, Kun Chen, Yangfan Li, Chenhao Ma. Efficient Maintenance of 2-Hop Labeling Index on Dynamic Small-World Graphs. Proceedings of the VLDB Endowment (PVLDB), 18(7): 2005-2017, 2025.
  7. Qiuyang Mang, Jingbang Chen, Hangrui Zhou, Yu Gao, Yingli Zhou, Qingyu Shi, Richard Peng, Yixiang Fang, Chenhao Ma. Efficient Historical Butterfly Counting in Large Temporal Bipartite Networks via Graph Structure-aware Index. Proceedings of the VLDB Endowment (PVLDB), 18(6): 1607-1620, 2025.
  8. Yankai Chen, Taotao Wang, Yixiang Fang*, Yunyu Xiao. Semi-supervised Node Importance Estimation with Informative Distribution Modeling for Uncertainty Regularization. The ACM Web Conference (formerly known as International World Wide Web Conference (WWW)), pages 3108-3118, 2025.
  9. Yuyang Liang, Yankai Chen, Yixiang Fang, Laks. V.S. Lakshmanan, Chenhao Ma. TRACE: Intra-visit Clinical Event Nowcasting via Effective Patient Trajectory Encoding. The ACM Web Conference (formerly known as International World Wide Web Conference (WWW)), pages 1118-1122, 2025.
  10. Yicheng Leng, Chaowei Fang, Junye Chen, Yixiang Fang, Sheng Li, Guanbin Li. Bridging Knowledge Gap between Image Inpainting and Large-Area Visible Watermark Removal. AAAI Conference on Artificial Intelligence (AAAI), 39(5): 4589-4597, 2025.
  11. Mengyao Li, Zhibang Yang, Xu Zhou, Yixiang Fang, Kenli Li, Keqin Li. Clustering on Attributed Graphs: From Single-view to Multi-view. ACM Computing Surveys, 57(7): 163:1-163:36, 2025.
  12. Yuanyuan Zeng, Yixiang Fang*, Chenhao Ma, Xu Zhou, Kenli Li. Efficient Distributed Hop-Constrained Path Enumeration on Large-Scale Graphs. ACM International Conference on Management of Data (SIGMOD), 2(1): 22:1-22:25, 2024.
  13. Chunxu Lin, Wensheng Luo, Yixiang Fang*, Chenhao Ma, Xilin Liu, Yuchi Ma. On Efficient Large Sparse Matrix Chain Multiplication. ACM International Conference on Management of Data (SIGMOD), 2(3): 119:2-119:27, 2024.
  14. Yingli Zhou, Qingshuo Guo, Yixiang Fang*, Chenhao Ma. A Counting-based Approach for Efficient k-Clique Densest Subgraph Discovery. ACM International Conference on Management of Data (SIGMOD), 2(3):156:2-156:27, 2024.
  15. Wensheng Luo, Qiaoyuan Yang, Yixiang Fang*, Xu Zhou. Efficient Core Maintenance in Large Bipartite Graphs. ACM International Conference on Management of Data (SIGMOD), 1(3): 208:1-208:26, 2024.
  16. Yingli Zhou, Qingshuo Guo, Yi Yang, Yixiang Fang*, Chenhao Ma, Laks V.S. Lakshmanan. In-depth Analysis of Densest Subgraph Discovery in a Unified Framework. Proceedings of the VLDB Endowment (PVLDB), 18(4): 1131 - 1144, 2024.
  17. Zheng Wu, Xuliang Zhu, Yixiang Fang, Jianliang Xu, Xin Huang. Interactive Graph Search for Multiple Targets on DAGs. Proceedings of the VLDB Endowment (PVLDB), 18(4): 1091-1103, 2025.
  18. Yingli Zhou, Yixiang Fang*, Chenhao Ma, Tianci Hou, Xin Huang. Efficient Maximal Motif-Clique Enumeration over Large Heterogeneous Information Networks. Proceedings of the VLDB Endowment (PVLDB), 17(11): 2946-2959, 2024.
  19. Wensheng Luo, Yixiang Fang*, Chunxu Lin, Yingli Zhou. Efficient Parallel D-core Decomposition at Scale. Proceedings of the VLDB Endowment (PVLDB), 17(10): 2654-2667, 2024.
  20. Yuanyuan Zeng, Chenhao Ma, Yixiang Fang. Distributed Shortest Distance Labeling on Large-Scale Graphs. Proceedings of the VLDB Endowment (PVLDB), 17(10): 2641-2653, 2024.
  21. Yucan Guo, Chenhao Ma, Yixiang Fang. Efficient Core Decomposition over Large Heterogeneous Information Networks. IEEE International Conference on Data Engineering (ICDE), pages 2393-2406, 2024.
  22. Jiayang Pang, Chenhao Ma, Yixiang Fang. A Similarity-based Approach for Efficient Large Quasi-clique Detection. The ACM Web Conference (formerly known as International World Wide Web Conference (WWW)), pages 401-409, 2024.
  23. Yankai Chen, Yixiang Fang*, Qiongyan Wang, Xin Cao, Irwin King. Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks. AAAI Conference on Artificial Intelligence (AAAI), pages 8302-8310, 2024.
  24. Xinni Zhang, Yankai Chen, Chenhao Ma, Yixiang Fang, Irwin King. Influential Exemplar Replay for Incremental Learning in Recommender Systems. AAAI Conference on Artificial Intelligence (AAAI), pages 9368-9376, 2024.
  25. Yicheng Leng, Chaowei Fang, Gen Li, Yixiang Fang, Guanbin Li. Removing Interference and Recovering Content Imaginatively for Visible Watermark Removal. AAAI Conference on Artificial Intelligence (AAAI), pages 2983-2990, 2024.
  26. Yankai Chen, Yixiang Fang, Yifei Zhang, Chenhao Ma, Yang Hong, Irwin King. Towards Effective Top-N Hamming Search via Bipartite Graph Contrastive Hashing. IEEE Transactions on Knowledge and Data Engineering (TKDE), 36(12): 9418-9432, 2024.
  27. Yuren Mao, Yu Hao, Xin Cao, Yixiang Fang, Xuemin Lin, Hua Mao, Zhiqiang Xu. Dynamic Graph Embedding via Meta-Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 36(7): 2967-2979, 2024.
  28. Yichen Xu, Chenhao Ma, Yixiang Fang, Zhifeng Bao. Efficient and Effective Algorithms for Densest Subgraph Discovery and Maintenance. The VLDB Journal (VLDBJ), 33(5): 1427-1452, 2024.
  29. Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V.S. Lakshmanan, Xiaolin Han, Xiaodong Li. Accelerating Directed Densest Subgraph Queries with Software and Hardware Approaches. The VLDB Journal (VLDBJ), 33(1): 207-230, 2024.
  30. Haoxuan Xie, Yixiang Fang*, Yuyang Xia, Wensheng Luo, Chenhao Ma. On Querying Connected Components in Large Temporal Graphs. ACM International Conference on Management of Data (SIGMOD), 1(2):170:1-170:27, 2023.
  31. Yichen Xu, Chenhao Ma, Yixiang Fang, Zhifeng Bao. Efficient and Effective Algorithms for Generalized Densest Subgraph Discovery. ACM International Conference on Management of Data (SIGMOD), 1(2):169:1-169:27, 2023.
  32. Yufan Sheng, Xin Cao, Yixiang Fang, Kaiqi Zhao, Jianzhong Qi, Gao Cong, Wenjie Zhang. WISK: A Workload-aware Learned Index for Spatial Keyword Queries. ACM International Conference on Management of Data (SIGMOD), 1(2):187:1-187:27, 2023.
  33. Yingli Zhou, Yixiang Fang*, Wensheng Luo, Yunming Ye. Influential Community Search over Large Heterogeneous Information Networks. Proceedings of the VLDB Endowment (PVLDB), 16(8): 2047-2060, 2023.
  34. Yankai Chen, Yixiang Fang, Yifei Zhang, Irwin King. Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space. The ACM Web Conference (formerly known as International World Wide Web Conference (WWW)), pages 3164-3172, 2023.
  35. Wensheng Luo, Zhuo Tang, Yixiang Fang, Chenhao Ma, Xu Zhou. Scalable Algorithms for Densest Subgraph Discovery. IEEE International Conference on Data Engineering (ICDE), pages 285-298, 2023.
  36. Tongfeng Weng, Xu Zhou, Yixiang Fang, Kian-Lee Tan, Kenli Li. Finding Top-k Important Edges on Bipartite Graphs: Ego-betweenness Centrality-based Approaches. IEEE International Conference on Data Engineering (ICDE), pages 2406-2419, 2023.
  37. Linhao Luo, Yixiang Fang*, Moli Lu, Xin Cao, Xiaofeng Zhang, Wenjie Zhang. GSim: A Graph Neural Network based Relevance Measure for Heterogeneous Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE), 35(12):12693-12707, 2023.
  38. Yixiang Fang, Kai Wang, Xuemin Lin, Wenjie Zhang. Cohesive Subgraph Search over Big Heterogeneous Information Networks. Springer Briefs in Computer Science, Springer, ISBN 978-3-030-97567-8, pages 1-63, 2022.
  39. Chenhao Ma, Yixiang Fang*, Reynold Cheng, Laks V.S. Lakshmanan, Xiaolin Han. A Convex-Programming Approach for Efficient Directed Densest Subgraph Discovery. ACM International Conference on Management of Data (SIGMOD), pages 845-859, 2022.
  40. Yixiang Fang, Wensheng Luo, Chenhao Ma. Densest Subgraph Discovery on Large Graphs: Applications, Challenges, and Techniques. Proceedings of the VLDB Endowment (PVLDB), 15(12): 3766-3769, 2022.
  41. Yangqin Jiang, Yixiang Fang*, Chenhao Ma, Xin Cao, Chunshan Li. Effective Community Search over Large Star-Schema Heterogeneous Information Networks. Proceedings of the VLDB Endowment (PVLDB), 15(11): 2307-2320, 2022.
  42. Chenji Huang, Yixiang Fang*, Xuemin Lin, Xin Cao, Wenjie Zhang, Maria Orlowska. Estimating Node Importance Values in Heterogeneous Information Networks. IEEE International Conference on Data Engineering (ICDE), pages 846-858, 2022.
  43. Xuefeng Chen, Xin Cao, Yifeng Zeng, Yixiang Fang, Sibo Wang, Xuemin Lin, Liang Feng. Constrained Path Search with Submodular Function Maximization. IEEE International Conference on Data Engineering (ICDE), pages 325-337, 2022.
  44. Yixiang Fang, Kai Wang, Xuemin Lin, Wenjie Zhang. Cohesive Subgraph Search over Big Heterogeneous Information Networks: Applications, Challenges, and Solutions. ACM International Conference on Management of Data (SIGMOD), pages 2829-2838, 2021.
  45. Chenhao Ma, Yixiang Fang*, Reynold Cheng, Laks V.S. Lakshmanan, Wenjie Zhang, Xuemin Lin. On Directed Densest Subgraph Discovery. ACM Transactions on Database Systems (TODS), 46(3):13:1-13:45, 2021.
  46. Yixing Yang, Yixiang Fang*, Maria Orlowska, Wenjie Zhang, Xuemin Lin. Efficient Bi-triangle Counting for Large Bipartite Networks. Proceedings of the VLDB Endowment (PVLDB), 14(6): 984-996, 2021.
  47. Yu Hao, Xin Cao, Yufan Sheng, Yixiang Fang, Wei Wang. KS-GNN: Keywords Search over Incomplete Graphs via Graphs Neural Network. The Annual Conference on Neural Information Processing Systems (NeurIPS), pages 1700-1712, 2021.
  48. Chenhao Ma, Yixiang Fang, Reynold Cheng, Laks V.S. Lakshmanan, Wenjie Zhang, Xuemin Lin. Efficient Directed Densest Subgraph Discovery. ACM SIGMOD Record, 50(1):33-40, 2021. (ACM SIGMOD Research Highlight Award, Here is a technical perspective of this work written by Prof. Yufei Tao)
  49. Bolong Zheng, Lingfeng Ming, Qi Hu, Yixiang Fang, Kai Zheng, Guohui Li. Dynamic Taxi Route Planning based on Deep Reinforcement Learning. International Conference on Spatial Data and Intelligence (SpatialDI)/Journal of Computer Research and Development, 2021. (Best Paper Award)
  50. Linhao Luo, Yixiang Fang*, Xin Cao, Xiaofeng Zhang, Wenjie Zhang. CP-GNN: A Software for Community Detection in Heterogeneous Information Networks. Software Impacts, 2021.
  51. Yixiang Fang, Yixing Yang, Wenjie Zhang, Xuemin Lin, Xin Cao. Effective and Efficient Community Search over Large Heterogeneous Information Networks. Proceedings of the VLDB Endowment (PVLDB), 13(6):854-867, 2020.
  52. Yixiang Fang, Xin Huang, Lu Qin, Ying Zhang, Wenjie Zhang, Reynold Cheng, Xuemin Lin. A Survey of Community Search Over Big Graphs. The VLDB Journal (VLDBJ), 29(1): 353-392, 2020.
  53. Chenhao Ma, Yixiang Fang*, Reynold Cheng, Laks V.S. Lakshmanan, Wenjie Zhang, Xuemin Lin. Efficient Algorithms for Densest Subgraph Discovery on Large Directed Graphs. ACM International Conference on Management of Data (SIGMOD), pages 1051-1066, 2020. (One of the Four Best Papers; rate: ~4/458)
  54. Yixing Yang, Yixiang Fang*, Xuemin Lin, Wenjie Zhang. Effective and Efficient Truss Computation Over Large Heterogeneous Information Networks. IEEE International Conference on Data Engineering (ICDE), pages 901-912, 2020.
  55. Boxuan Li, Reynold Cheng, Jiafeng Hu, Yixiang Fang, Min Ou, Ruibang Luo, Kevin C.C. Chang, Xuemin Lin. MC-Explorer: Analyzing and Visualizing Motif-Cliques on Large Networks. IEEE International Conference on Data Engineering (ICDE), pages 1722-1725, 2020.
  56. Yankai Chen, Jie Zhang, Yixiang Fang*, Xin Cao, Irwin King. Efficient Community Search over Large Directed Graph: An Augmented Index-based Approach. International Joint Conferences on Artificial Intelligence (IJCAI), pages 3544-3550, 2020.
  57. Yu Hao, Xin Cao, Yixiang Fang*, Xike Xie, Sibo Wang. Inductive Link Prediction for Nodes with Only Attribute Information. International Joint Conferences on Artificial Intelligence (IJCAI), pages 1209-1215, 2020.
  58. Xuefeng Chen, Xin Cao, Yifeng Zeng, Yixiang Fang, Bin Yao. Optimal Region Search with Submodular Maximization. International Joint Conferences on Artificial Intelligence (IJCAI), pages 1216-1222, 2020.
  59. Hongmei Chen, Yixiang Fang, Ying Zhang, Wenjie Zhang, Lizhen Wang. ESPM: Efficient Spatial Pattern Matching. IEEE Transactions on Knowledge and Data Engineering (TKDE), 32(6): 1227-1233, 2020.
  60. Yixiang Fang, Kaiqiang Yu, Reynold Cheng, Laks V.S. Lakshmanan, Xuemin Lin. Efficient Algorithms for Densest Subgraph Discovery. Proceedings of the VLDB Endowment (PVLDB), 12(11): 1719-1732, 2019. [Codes are available via email request]
  61. Yixiang Fang, Yun Li, Reynold Cheng, Nikos Mamoulis, Gao Cong. Evaluating Pattern Matching Queries for Spatial Databases. The VLDB Journal (VLDBJ), 28(5): 649-673, 2019.
  62. Yixiang Fang, Zhongran Wang, Reynold Cheng, Hongzhi Wang, Jiafeng Hu. Effective and Efficient Community Search over Large Directed Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(11): 2093-2107, 2019.
  63. Yixiang Fang, Zheng Wang, Reynold Cheng, Xiaodong Li, Siqiang Luo, Jiafeng Hu, Xiaojun Chen. On Spatial-Aware Community Search. IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(4): 783-798, 2019.
  64. Yankai Chen, Yixiang Fang*, Reynold Cheng, Yun Li, Xiaojun Chen, Jie Zhang. Exploring Communities in Large Profiled Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(8): 1624-1629, 2019.
  65. Chenhao Ma, Reynold Cheng, Laks V.S. Lakshmanan, Tobias Grubenmann, Yixiang Fang*, Xiaodong Li. LINC: A Motif Counting Algorithm for Uncertain Graphs. Proceedings of the VLDB Endowment (PVLDB), 13(2): 155-168, 2019.
  66. Jiafeng Hu, Reynold Cheng, Kevin C.C. Chang, Aravind Sankar, Yixiang Fang*, Brian Y. H. Lam. Discovering Maximal Motif Cliques in Large Heterogeneous Information Networks. IEEE International Conference on Data Engineering (ICDE), pages 746-757, 2019.
  67. Yixiang Fang, Reynold Cheng, Gao Cong, Nikos Mamoulis, Yun Li. On Spatial Pattern Matching. IEEE International Conference on Data Engineering (ICDE), pages 293-304, 2018. [Codes are available via email request]
  68. Yixiang Fang, Reynold Cheng, Jikun Wang, Budiman, Gao Cong, Nikos Mamoulis. SpaceKey: Exploring Patterns in Spatial Databases. IEEE International Conference on Data Engineering (ICDE), pages 1577-1580, 2018.
  69. Xiaojun Chen, Yixiang Fang, Min Yang, Feiping Nie, Zhou Zhao, Joshua Zhexue Huang. PurTreeClust: A Clustering Algorithm for Customer Segmentation from Massive Customer Transaction Data. IEEE Transactions on Knowledge and Data Engineering (TKDE), 30(3): 559-572, 2018.
  70. Yixiang Fang, Reynold Cheng, Xiaodong Li, Siqiang Luo, Jiafeng Hu. Effective Community Search over Large Spatial Graphs. Proceedings of the VLDB Endowment (PVLDB), 10(6): 709-720, 2017. [Codes are available via email request]
  71. Yixiang Fang, Reynold Cheng, Siqiang Luo, Jiafeng Hu, Kai Huang. C-Explorer: Browsing Communities in Large Graphs. Proceedings of the VLDB Endowment (PVLDB), 10(12): 1885-1888, 2017.
  72. Yixiang Fang, Reynold Cheng, Yankai Chen, Siqiang Luo, Jiafeng Hu. Effective and Efficient Attributed Community Search. The VLDB Journal (VLDBJ), 26(6): 803-828, 2017.
  73. Jiafeng Hu, Xiaowei Wu, Reynold Cheng, Siqiang Luo, Yixiang Fang. On Minimal Steiner Maximum-Connected Subgraph Queries. IEEE Transactions on Knowledge and Data Engineering (TKDE), 29(11): 2455-2469, 2017.
  74. Yixiang Fang, Reynold Cheng, Wenbin Tang, Silviu Maniu, Xuan Yang. Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data. IEEE Transactions on Knowledge and Data Engineering (TKDE), 28(3): 785-800, 2016.
  75. Yixiang Fang, Reynold Cheng, Siqiang Luo, Jiafeng Hu. Effective Community Search for Large Attributed Graphs. Proceedings of the VLDB Endowment (PVLDB), 9(12): 1233-1244, 2016. [Codes are available via email request]
  76. Zhenguo Li, Yixiang Fang, Qin Liu, Jiefeng Cheng, Reynold Cheng, John C.S. Lui. Walking in the Cloud: Parallel SimRank at Scale. Proceedings of the VLDB Endowment (PVLDB), 9(1): 24-35, 2015.

Team

PostDoc researchers
PhD students
MPhil students
Undergraduate students

Teaching

Academic year 2024-2025
Academic year 2023-2024
Academic year 2022-2023
Academic year 2021-2022
Academic year 2020-2021

Teaching Honors

Service

Journal editorship
Conference organizer
Conference program committee members
Journal reviewers