Xiaojun Kang

2.4k total citations
64 papers, 1.5k citations indexed

About

Xiaojun Kang is a scholar working on Artificial Intelligence, Plant Science and Molecular Biology. According to data from OpenAlex, Xiaojun Kang has authored 64 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 18 papers in Plant Science and 16 papers in Molecular Biology. Recurrent topics in Xiaojun Kang's work include Plant Molecular Biology Research (12 papers), Advanced Graph Neural Networks (10 papers) and Topic Modeling (7 papers). Xiaojun Kang is often cited by papers focused on Plant Molecular Biology Research (12 papers), Advanced Graph Neural Networks (10 papers) and Topic Modeling (7 papers). Xiaojun Kang collaborates with scholars based in China, United States and France. Xiaojun Kang's co-authors include Min Ni, Paul F. Robbins, Steven A. Rosenberg, Yutaka Kawakami, Yun Zhou, Xiaodong Sun, Junhua Ding, Xiansheng Zhang, Xiang Zhao and Xiaojuan Zhang and has published in prestigious journals such as Nature Communications, The Journal of Experimental Medicine and SHILAP Revista de lepidopterología.

In The Last Decade

Xiaojun Kang

59 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaojun Kang China	19	684	642	345	132	131	64	1.5k
Chaoyang Wang China	21	119 0.2×	1.2k 1.9×	92 0.3×	126 1.0×	110 0.8×	87	1.9k
Yunhao Liu China	22	241 0.4×	434 0.7×	60 0.2×	127 1.0×	33 0.3×	66	1.9k
Claudio Lottaz Germany	21	232 0.3×	1.6k 2.5×	658 1.9×	121 0.9×	310 2.4×	33	3.0k
Atsushi Iwasaki Japan	19	107 0.2×	548 0.9×	396 1.1×	95 0.7×	152 1.2×	76	1.9k
Jianguang Zhang China	24	849 1.2×	657 1.0×	107 0.3×	105 0.8×	200 1.5×	114	2.5k
Xiaoling Xia China	19	120 0.2×	289 0.5×	102 0.3×	170 1.3×	152 1.2×	84	1.2k
Jae Woo Choi South Korea	19	84 0.1×	996 1.6×	136 0.4×	51 0.4×	314 2.4×	34	1.6k
Shihao Shen United States	26	328 0.5×	3.1k 4.8×	170 0.5×	45 0.3×	191 1.5×	49	3.9k
Yuanning Liu China	19	412 0.6×	1.5k 2.4×	122 0.4×	235 1.8×	34 0.3×	62	2.5k
Carlo Bergamini Italy	17	341 0.5×	571 0.9×	92 0.3×	13 0.1×	332 2.5×	41	1.3k

Countries citing papers authored by Xiaojun Kang

Since Specialization

Citations

This map shows the geographic impact of Xiaojun Kang'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 Xiaojun Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojun Kang more than expected).

Fields of papers citing papers by Xiaojun Kang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiaojun Kang. 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 Xiaojun Kang. The network helps show where Xiaojun Kang may publish in the future.

Co-authorship network of co-authors of Xiaojun Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaojun Kang. A scholar is included among the top collaborators of Xiaojun Kang 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 Xiaojun Kang. Xiaojun Kang 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

Liu, Yanmei, Huiying Cao, Jian Zhang, et al.. (2025). AIP, fatty liver, and HbA1c as modifiers of the C-index and diabetes risk relationship. Lipids in Health and Disease. 24(1). 129–129. 1 indexed citations

Kang, Xiaojun, et al.. (2025). Sparse-MoE-SAM: A Lightweight Framework Integrating MoE and SAM with a Sparse Attention Mechanism for Plant Disease Segmentation in Resource-Constrained Environments. Plants. 14(17). 2634–2634. 1 indexed citations

Kang, Xiaojun, et al.. (2024). Accusations and Law Articles Prediction in the Field of Environmental Protection. Applied Sciences. 15(1). 280–280.

Yang, Cheng, et al.. (2024). LAAP: Learning the Argument of An Entity with Event Prompts for document-level event extraction. Neurocomputing. 613. 128584–128584. 2 indexed citations

Minami, Anzu, Xiaojun Kang, & Clay J. Carter. (2021). A cell wall invertase controls nectar volume and sugar composition. The Plant Journal. 107(4). 1016–1028. 24 indexed citations

Dong, Lijun, et al.. (2021). Anchors-Based Incremental Embedding for Growing Knowledge Graphs. IEEE Transactions on Knowledge and Data Engineering. 35(4). 3458–3470. 9 indexed citations

Weiss, Trevor, Xiaojun Kang, Hui Zhao, et al.. (2020). Optimization of multiplexed CRISPR/Cas9 system for highly efficient genome editing in Setaria viridis. The Plant Journal. 104(3). 828–838. 45 indexed citations

Kang, Xiaojun, et al.. (2020). A Neural-Network-Based Model of Charge Prediction via the Judicial Interpretation of Crimes. IEEE Access. 8. 101569–101579. 9 indexed citations

Xu, Gang, et al.. (2019). SHB1 and CCA1 interaction desensitizes light responses and enhances thermomorphogenesis. Nature Communications. 10(1). 3110–3110. 53 indexed citations

10.

Ding, Junhua, Xiaojun Kang, & Xin‐Hua Hu. (2017). Validating a Deep Learning Framework by Metamorphic Testing. 28–34. 42 indexed citations

11.

Kang, Xiaojun, Wei Li, Yun Zhou, & Min Ni. (2013). A WRKY Transcription Factor Recruits the SYG1-Like Protein SHB1 to Activate Gene Expression and Seed Cavity Enlargement. PLoS Genetics. 9(3). e1003347–e1003347. 64 indexed citations

12.

Liu, Zhihong, Xiaojun Kang, Zhe Lin, & Li Song. (2013). Research and implementation of simulation for TDICCD remote sensing in vibration of optical axis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9045. 90451E–90451E. 2 indexed citations

13.

He, Peng, et al.. (2012). A trust value measurement model based on group preference for green e-commerce network. World Automation Congress. 353–357. 1 indexed citations

14.

Sun, Xiaodong, Xiaojun Kang, & Min Ni. (2012). Hypersensitive to Red and Blue 1 and Its Modification by Protein Phosphatase 7 Are Implicated in the Control of Arabidopsis Stomatal Aperture. PLoS Genetics. 8(5). e1002674–e1002674. 20 indexed citations

15.

Kang, Xiaojun. (2011). Research on Evaluation of Professional Title Based on Service-oriented Architecture. Ke-ji guanli yanjiu.

16.

Yi, Wei, Yang Sun, Xufeng Wei, et al.. (2010). Proteomic profiling of human bone marrow mesenchymal stem cells under shear stress. Molecular and Cellular Biochemistry. 341(1-2). 9–16. 26 indexed citations

17.

Wei, Xufeng, Wei Yi, Chunhu Gu, et al.. (2009). RGD-modified acellular bovine pericardium as a bioprosthetic scaffold for tissue engineering. Journal of Materials Science Materials in Medicine. 20(11). 2327–2336. 82 indexed citations

18.

Kang, Xiaojun, Yun Zhou, Xiaodong Sun, & Min Ni. (2007). HYPERSENSITIVE TO RED AND BLUE 1 and its C‐terminal regulatory function control FLOWERING LOCUS T expression. The Plant Journal. 52(5). 937–948. 14 indexed citations

19.

Kang, Xiaojun & Min Ni. (2006). ArabidopsisSHORT HYPOCOTYL UNDER BLUE1 Contains SPX and EXS Domains and Acts in Cryptochrome Signaling. The Plant Cell. 18(4). 921–934. 69 indexed citations

20.

Robbins, Paul F., et al.. (1995). Identification of a gene encoding a melanoma tumor antigen recognized by HLA-A31-restricted tumor-infiltrating lymphocytes.. The Journal of Experimental Medicine. 181(2). 799–804. 233 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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