Le Yu

1.7k total citations
46 papers, 825 citations indexed

About

Le Yu is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Plant Science. According to data from OpenAlex, Le Yu has authored 46 papers receiving a total of 825 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 9 papers in Electrical and Electronic Engineering and 8 papers in Plant Science. Recurrent topics in Le Yu's work include Advanced Graph Neural Networks (8 papers), Research in Cotton Cultivation (7 papers) and Recommender Systems and Techniques (4 papers). Le Yu is often cited by papers focused on Advanced Graph Neural Networks (8 papers), Research in Cotton Cultivation (7 papers) and Recommender Systems and Techniques (4 papers). Le Yu collaborates with scholars based in China, United Kingdom and United States. Le Yu's co-authors include Leilei Sun, Bowen Du, Xiao Hu, Weifeng Lv, Liangzhe Han, David W. Burt, Xuxiang Ta, Andrew Loudon, J.R. Davis and Katarzyna Miedzinska and has published in prestigious journals such as PLANT PHYSIOLOGY, Clinical Infectious Diseases and Current Biology.

In The Last Decade

Le Yu

40 papers receiving 810 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Le Yu China	13	204	159	151	115	113	46	825
Maryam Hafeez United Kingdom	20	33 0.2×	74 0.5×	85 0.6×	16 0.1×	88 0.8×	67	1.1k
Honglei Ren China	18	117 0.6×	322 2.0×	44 0.3×	37 0.3×	408 3.6×	55	1.0k
Yingshi Guo China	13	81 0.4×	92 0.6×	38 0.3×	74 0.6×	104 0.9×	60	668
Guijuan Wang China	15	39 0.2×	97 0.6×	63 0.4×	25 0.2×	206 1.8×	64	616
Wenhui Zhang China	13	232 1.1×	89 0.6×	36 0.2×	211 1.8×	132 1.2×	47	747
Pascale Kuntz France	16	155 0.8×	30 0.2×	204 1.4×	78 0.7×	40 0.4×	38	976
Fabien Michel France	21	13 0.1×	76 0.5×	136 0.9×	43 0.4×	56 0.5×	75	995
Timothy T Weil United Kingdom	14	81 0.4×	597 3.8×	73 0.5×	52 0.5×	61 0.5×	27	1.8k
Jorge Vera Chile	19	26 0.1×	65 0.4×	26 0.2×	20 0.2×	53 0.5×	39	930
Xiaoqing Han China	21	49 0.2×	32 0.2×	122 0.8×	4 0.0×	60 0.5×	161	1.9k

Countries citing papers authored by Le Yu

Since Specialization

Citations

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

Fields of papers citing papers by Le Yu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Le Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Le Yu. A scholar is included among the top collaborators of Le Yu 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 Le Yu. Le Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Wang, Jianji, et al.. (2025). GL-MSIN: A Global–Local Hierarchical Multiscale Interaction Network for Referring Remote Sensing Image Segmentation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 27193–27207.

Zhang, Xiao, Dongmei Li, Le Yu, et al.. (2025). The effect of 254 nm ultraviolet C promoting ethanol-induced gastric injury healing - A potential physical factor therapy. Journal of Photochemistry and Photobiology B Biology. 267. 113164–113164.

Yu, Le, Meiling Chen, De Zhu, et al.. (2025). Transcriptional Regulation of SWEET15_A01 by MYB44 / bHLH3 Modulates Carbon Allocation in Cotton Ovule and Fibre to Affect Seed and Fibre Traits. Plant Biotechnology Journal. 24(3). 1769–1791.

Zhou, Kun, Meng Wu, Han Qiao, et al.. (2025). Disulfidptosis-related genes RPN1 inhibits the progression of hepatocellular carcinoma by regulating cell cycle, may be a new therapeutic targets. Inflammation Research. 74(1). 105–105.

Xu, Zhiyong, Chao Fu, Ruiting Zhang, et al.. (2025). NAC transcription factor GbNTL9 modifies the accumulation and organization of cellulose microfibrils to enhance cotton fiber strength. Journal of Advanced Research. 78. 95–109. 2 indexed citations

Peng, Dailiang, Jing M. Chen, Alfredo Huete, et al.. (2025). High-precision inversion of vegetation parameters in the AI era: Integrating hyperspectral remote sensing and deep learning. The Innovation. 6(6). 100868–100868. 3 indexed citations

Xiao, Xi, et al.. (2025). Revolutionizing Encrypted Traffic Classification with MH-Net: A Multi-View Heterogeneous Graph Model. Proceedings of the AAAI Conference on Artificial Intelligence. 39(1). 1048–1056. 1 indexed citations

Wu, Peng, Le Yu, Xiaomei Yi, et al.. (2024). Research on WSN reliable ranging and positioning algorithm for forest environment. Scientific Reports. 14(1). 5417–5417. 2 indexed citations

Yu, Le, et al.. (2024). Consumer Electronics and GenAI Providing User Experiences in Mental Health. IEEE Consumer Electronics Magazine. 14(5). 84–93. 3 indexed citations

10.

Yu, Le, et al.. (2023). A Reliable Energy Trading Strategy in Intelligent Microgrids Using Deep Reinforcement Learning. Computers & Electrical Engineering. 110. 108796–108796. 6 indexed citations

11.

Yu, Le, et al.. (2023). Predicting Temporal Sets with Simplified Fully Connected Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 37(4). 4835–4844. 2 indexed citations

12.

Lü, Xiaodong, et al.. (2023). Continuous-Time Graph Learning for Cascade Popularity Prediction. 2224–2232. 6 indexed citations

13.

Yang, Yang, Chunyuan You, Nian Wang, et al.. (2023). Gossypium mustelinum genome and an introgression population enrich interspecific genetics and breeding in cotton. Theoretical and Applied Genetics. 136(6). 130–130. 4 indexed citations

14.

Yu, Le, et al.. (2023). Event-Based Dynamic Graph Representation Learning for Patent Application Trend Prediction. IEEE Transactions on Knowledge and Data Engineering. 36(5). 1951–1963. 8 indexed citations

15.

Zhang, Beibei, Tian Yao, Chao Shen, et al.. (2022). Re enhances anthocyanin and proanthocyanidin accumulation to produce red foliated cotton and brown fiber. PLANT PHYSIOLOGY. 189(3). 1466–1481. 28 indexed citations

16.

Du, Bowen, et al.. (2021). Modelling the epidemic dynamics of COVID-19 with consideration of human mobility. International Journal of Data Science and Analytics. 12(4). 369–382. 12 indexed citations

17.

Yu, Le, Bowen Du, Xiao Hu, et al.. (2019). Traffic Accident Prediction Based on Deep Spatio-Temporal Analysis. 995–1002. 5 indexed citations

18.

Li, Ying, Yongzhi Yang, Le Yu, Xin Du, & Guangpeng Ren. (2018). Plastomes of nine hornbeams and phylogenetic implications. Ecology and Evolution. 8(17). 8770–8778. 15 indexed citations

19.

Wood, Shona H., Helen Christian, Katarzyna Miedzinska, et al.. (2015). Binary Switching of Calendar Cells in the Pituitary Defines the Phase of the Circannual Cycle in Mammals. Current Biology. 25(20). 2651–2662. 88 indexed citations

20.

Mou, Chunyan, Frédérique Pitel, David Gourichon, et al.. (2011). Cryptic Patterning of Avian Skin Confers a Developmental Facility for Loss of Neck Feathering. PLoS Biology. 9(3). e1001028–e1001028. 88 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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