Kun Lü

1.5k total citations · 1 hit paper
96 papers, 937 citations indexed

About

Kun Lü is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Kun Lü has authored 96 papers receiving a total of 937 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Artificial Intelligence, 23 papers in Molecular Biology and 21 papers in Information Systems. Recurrent topics in Kun Lü's work include Biomedical Text Mining and Ontologies (15 papers), Topic Modeling (14 papers) and scientometrics and bibliometrics research (14 papers). Kun Lü is often cited by papers focused on Biomedical Text Mining and Ontologies (15 papers), Topic Modeling (14 papers) and scientometrics and bibliometrics research (14 papers). Kun Lü collaborates with scholars based in United States, China and Canada. Kun Lü's co-authors include Dietmar Wolfram, Jin Mao, Xiangming Mu, Gang Li, Soohyung Joo, Isola Ajiferuke, J. Zaborszky, G. Huang, Guancan Yang and Margaret E. I. Kipp and has published in prestigious journals such as PLoS ONE, The Science of The Total Environment and Chemical Engineering Journal.

In The Last Decade

Kun Lü

84 papers receiving 897 citations

Hit Papers

Municipal solid waste man... 2024 2026 2024 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Municipal solid waste management challenges in developing regions: A comprehensive review and future perspectives for Asia and Africa
    2024 112 citations Zhonghao Chen, Jiawen Zhang et al. The Science of The Total Environment profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kun Lü 247 176 119 102 76 96 937
Shuo Xu 562 2.3× 185 1.1× 168 1.4× 145 1.4× 81 1.1× 100 1.5k
Katsumori Matsushima 173 0.7× 156 0.9× 201 1.7× 105 1.0× 229 3.0× 35 1.4k
Xuefeng Wang 135 0.5× 86 0.5× 128 1.1× 123 1.2× 39 0.5× 144 1.4k
Per Ahlgren 256 1.0× 244 1.4× 344 2.9× 107 1.0× 176 2.3× 59 1.4k
Bo Jarneving 154 0.6× 216 1.2× 251 2.1× 65 0.6× 154 2.0× 15 1.1k
Sungchul Choi 367 1.5× 187 1.1× 33 0.3× 67 0.7× 43 0.6× 66 2.4k
Wanru Wang 118 0.5× 54 0.3× 62 0.5× 42 0.4× 49 0.6× 27 709
Nils C. Newman 165 0.7× 132 0.8× 151 1.3× 75 0.7× 85 1.1× 47 1.1k
Xin An 179 0.7× 44 0.3× 106 0.9× 69 0.7× 42 0.6× 34 644

Countries citing papers authored by Kun Lü

Since Specialization
Citations

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

Fields of papers citing papers by Kun Lü

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kun Lü

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

All Works

20 of 20 papers shown
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2.
Lü, Kun, et al.. (2025). Constructing surrogates for atomistic simulations via deep learning and generative large language models. Journal of materials research/Pratt's guide to venture capital sources. 41(1). 180–196. 1 indexed citations
3.
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Yang, Guancan, Di Liu, Ling Chen, & Kun Lü. (2024). Integrating persistence process into the analysis of technology convergence using STERGM. Journal of Informetrics. 19(1). 101632–101632.
5.
Zhang, Xiaoxuan, Zengfu Wang, Mingyue Ji, et al.. (2024). A sea–land clutter classification framework for over-the-horizon radar based on weighted loss semi-supervised generative adversarial network. Engineering Applications of Artificial Intelligence. 133. 108526–108526. 4 indexed citations
6.
Song, Tiecheng, et al.. (2024). Range-Doppler image classification for interference detection in over-the-horizon radar. Digital Signal Processing. 155. 104727–104727. 1 indexed citations
7.
Huang, Liangliang, et al.. (2024). How Does a Generative Large Language Model Perform on Domain-Specific Information Extraction?─A Comparison between GPT-4 and a Rule-Based Method on Band Gap Extraction. Journal of Chemical Information and Modeling. 64(20). 7895–7904. 9 indexed citations
8.
Wan, Changxuan, Keli Xiao, Kun Lü, et al.. (2024). Dependency Structure-Enhanced Graph Attention Networks for Event Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 38(17). 19098–19106. 1 indexed citations
9.
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Chen, Zhonghao, Jiawen Zhang, Yunfei Liu, et al.. (2024). Municipal solid waste management challenges in developing regions: A comprehensive review and future perspectives for Asia and Africa. The Science of The Total Environment. 930. 172794–172794. 112 indexed citations breakdown →
11.
Jiao, Yi, et al.. (2023). A bioinspired fluorescent probe based on metal–organic frameworks to selectively enrich and detect amyloid-β peptide. Chemical Engineering Journal. 470. 144124–144124. 7 indexed citations
12.
Li, Rongpeng, Kun Lü, Xianfu Chen, et al.. (2023). Semantics-Empowered Communications: A Tutorial-Cum-Survey. IEEE Communications Surveys & Tutorials. 26(1). 41–79. 53 indexed citations
13.
Mao, Jin, et al.. (2021). Finding citations for PubMed: a large-scale comparison between five freely available bibliographic data sources. Scientometrics. 126(12). 9519–9542. 20 indexed citations
14.
Lü, Kun, et al.. (2016). Research on Implied-trust Aware Collaborative Filtering Recommendation Algorithm. 37(2). 245. 3 indexed citations
15.
Lü, Kun, et al.. (2016). Integrated physiological model for mental workload assessment and prediction of aircraft flight deck display interface. Beijing Hangkong Hangtian Daxue xuebao. 42(4). 685. 2 indexed citations
16.
Yang, Lei, Shuyun Yang, Jibin Liu, et al.. (2014). Expression of GRP78 predicts taxane-based therapeutic resistance and recurrence of human gastric cancer. Experimental and Molecular Pathology. 96(2). 235–241. 21 indexed citations
17.
Mu, Xiangming, et al.. (2011). Supporting effective health and biomedical information retrieval and navigation: A novel facet view interface evaluation. Journal of Biomedical Informatics. 44(4). 576–586. 21 indexed citations
18.
Lü, Kun. (2008). Research on Externalization of Tacit Knowledge Based on Web 2.0. Information Sciences. 2 indexed citations
19.
Lü, Kun. (2007). Some Thoughts on the Teaching of Practical Writing in College English Teaching. 1 indexed citations
20.
Wu, Xiaolei, et al.. (2004). In Situ Synthesis of Nanocrystalline Intermetallic Compound Layer During Surface Mechanical Attrition Treatment of Zirconium. 中国科学院力学研究所. 25. 1 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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