Kangfei Zhao

604 total citations
26 papers, 258 citations indexed

About

Kangfei Zhao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics. According to data from OpenAlex, Kangfei Zhao has authored 26 papers receiving a total of 258 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 8 papers in Statistical and Nonlinear Physics. Recurrent topics in Kangfei Zhao's work include Advanced Graph Neural Networks (13 papers), Graph Theory and Algorithms (8 papers) and Complex Network Analysis Techniques (8 papers). Kangfei Zhao is often cited by papers focused on Advanced Graph Neural Networks (13 papers), Graph Theory and Algorithms (8 papers) and Complex Network Analysis Techniques (8 papers). Kangfei Zhao collaborates with scholars based in Hong Kong, China and United States. Kangfei Zhao's co-authors include Jeffrey Xu Yu, Hong Cheng, Lei Zou, Weiguo Zheng, Yu Rong, Junzhou Huang, Hao Zhang, Jianheng Tang, Qiyan Li and Hao Zhang and has published in prestigious journals such as Information Sciences, IEEE Transactions on Knowledge and Data Engineering and Neural Networks.

In The Last Decade

Kangfei Zhao

23 papers receiving 252 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Kangfei Zhao Hong Kong	10	195	93	53	44	40	26	258
Antonio Maccioni Italy	8	80 0.4×	77 0.8×	92 1.7×	26 0.6×	55 1.4×	16	173
Robert Pienta United States	8	76 0.4×	119 1.3×	37 0.7×	65 1.5×	27 0.7×	12	191
Bernhard Sch lkopf Germany	4	147 0.8×	40 0.4×	21 0.4×	68 1.5×	23 0.6×	4	234
Julien Leblay France	7	286 1.5×	64 0.7×	69 1.3×	17 0.4×	44 1.1×	13	333
Yifan Chen China	10	146 0.7×	79 0.8×	26 0.5×	19 0.4×	38 0.9×	26	246
Brigitte Boden Germany	7	134 0.7×	49 0.5×	59 1.1×	152 3.5×	67 1.7×	11	247
Zhongfei Mark Zhang United States	7	139 0.7×	80 0.9×	20 0.4×	59 1.3×	24 0.6×	9	229
Renchi Yang Hong Kong	9	212 1.1×	104 1.1×	67 1.3×	139 3.2×	36 0.9×	26	285
Xixun Lin China	10	291 1.5×	65 0.7×	39 0.7×	27 0.6×	16 0.4×	21	362
Hiroyuki Shinnou Japan	7	227 1.2×	50 0.5×	32 0.6×	16 0.4×	12 0.3×	49	288

Countries citing papers authored by Kangfei Zhao

Since Specialization

Citations

This map shows the geographic impact of Kangfei Zhao's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kangfei Zhao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kangfei Zhao more than expected).

Fields of papers citing papers by Kangfei Zhao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kangfei Zhao. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kangfei Zhao. The network helps show where Kangfei Zhao may publish in the future.

Co-authorship network of co-authors of Kangfei Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Kangfei Zhao. A scholar is included among the top collaborators of Kangfei Zhao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kangfei Zhao. Kangfei Zhao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Tan, Jie, Kangfei Zhao, Jeffrey Xu Yu, et al.. (2025). Can Large Language Models Be Query Optimizer for Relational Databases?. Proceedings of the ACM on Management of Data. 3(6). 1–28.

Yang, Han, Kangfei Zhao, Lanqing Li, et al.. (2024). Solving the non-submodular network collapse problems via Decision Transformer. Neural Networks. 176. 106328–106328.

Zhao, Kangfei, et al.. (2024). Feed: Towards Personalization-Effective Federated Learning. 1779–1791. 1 indexed citations

Zhao, Kangfei, et al.. (2024). Equivariant Line Graph Neural Network for Protein-Ligand Binding Affinity Prediction. IEEE Journal of Biomedical and Health Informatics. 28(7). 4336–4347. 2 indexed citations

Tan, Jie, Yu Rong, Kangfei Zhao, et al.. (2024). Natural Language-Assisted Multi-modal Medication Recommendation. arXiv (Cornell University). 2200–2209. 1 indexed citations

Zhao, Kangfei, et al.. (2024). Inductive Attributed Community Search: To Learn Communities Across Graphs. Proceedings of the VLDB Endowment. 17(10). 2576–2589. 2 indexed citations

Zhao, Kangfei, Jeffrey Xu Yu, Qiyan Li, Hao Zhang, & Yu Rong. (2023). Learned sketch for subgraph counting: a holistic approach. The VLDB Journal. 32(5). 937–962. 7 indexed citations

Zhao, Kangfei, et al.. (2023). Geometric Graph Learning for Protein Mutation Effect Prediction. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3412–3422. 2 indexed citations

Zhang, Zhiwei, et al.. (2023). Efficiently Counting Triangles for Hypergraph Streams by Reservoir-Based Sampling. IEEE Transactions on Knowledge and Data Engineering. 35(11). 11328–11341. 1 indexed citations

10.

Zhao, Kangfei, et al.. (2023). Community Search: A Meta-Learning Approach. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2358–2371. 6 indexed citations

11.

Zhao, Kangfei, et al.. (2023). Learning with Small Data: Subgraph Counting Queries. Data Science and Engineering. 8(3). 292–305. 1 indexed citations

12.

Tang, Jianheng, et al.. (2023). A Fused Gromov-Wasserstein Framework for Unsupervised Knowledge Graph Entity Alignment. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3320–3334. 11 indexed citations

13.

Zhao, Kangfei, et al.. (2022). Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process. Proceedings of the 2022 International Conference on Management of Data. 973–987. 11 indexed citations

14.

Zhao, Kangfei, Shengcai Liu, Jeffrey Xu Yu, & Yu Rong. (2021). Towards Feature-free TSP Solver Selection: A Deep Learning Approach. 1–8. 4 indexed citations

15.

Zhao, Kangfei, Zhiwei Zhang, Yu Rong, Jeffrey Xu Yu, & Junzhou Huang. (2021). Finding Critical Users in Social Communities via Graph Convolutions. IEEE Transactions on Knowledge and Data Engineering. 1–1. 11 indexed citations

16.

Zhao, Kangfei, Jeffrey Xu Yu, Hao Zhang, Qiyan Li, & Yu Rong. (2021). A Learned Sketch for Subgraph Counting. 2142–2155. 21 indexed citations

17.

Zhang, Hao, Jeffrey Xu Yu, Yikai Zhang, Kangfei Zhao, & Hong Cheng. (2020). Distributed subgraph counting. Proceedings of the VLDB Endowment. 13(12). 2493–2507. 14 indexed citations

18.

Zheng, Weiguo, Hong Cheng, Jeffrey Xu Yu, Lei Zou, & Kangfei Zhao. (2018). Interactive natural language question answering over knowledge graphs. Information Sciences. 481. 141–159. 47 indexed citations

19.

Zhao, Kangfei & Jeffrey Xu Yu. (2017). Graph Processing in RDBMSs.. IEEE Data(base) Engineering Bulletin. 40. 6–17. 4 indexed citations

20.

Zhao, Kangfei & Jeffrey Xu Yu. (2017). All-in-One. 1165–1180. 23 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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