Meng-kun Li

21 papers receiving 299 citations

Peers

Meng-kun Li
Comparison fields: 5 of 47
  • Computer Vision and Pattern Recognition 162
  • Statistics, Probability and Uncertainty 45
  • Safety, Risk, Reliability and Quality 41
  • Aerospace Engineering 110
  • Radiation 34
Replace Chun-li Xie with:
Chun-li Xie China
Nan Chao China
Alexandru Stancu United Kingdom
Graeme West United Kingdom
Jianping Ma Canada
Jingchao Peng China
Qi Dong China
Emine Ayaz Türkiye
Lee Yang United States
Qiao Yang China
Meng-kun Li relative to Chun-li Xie China Chun-li Xie's profile →
Citations per field
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Chun-li Xie · 1×
Citations per year

Countries citing papers authored by Meng-kun Li

Since Specialization
Citations

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

Fields of papers citing papers by Meng-kun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Meng-kun Li. 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 Meng-kun Li. The network helps show where Meng-kun Li may publish in the future.

Co-authors

The 19 scholars most cited alongside Meng-kun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Meng-kun Li Line = papers co-authored together Meng-kun Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201453
2 201550
3 201532
4 201631
5 201630
6 201818
7 201913
8 201812
9 20169
10 20218
11 20188
12 20218
13 20197
14 20196
15 20196
16 20206
17 20215
18 20234
19 20183
20 20241

About Meng-kun Li

Meng-kun Li is a scholar working on Control and Systems Engineering, Statistics, Probability and Uncertainty, Materials Chemistry, Computer Vision and Pattern Recognition and Pulmonary and Respiratory Medicine, having authored 21 papers that have together received 311 indexed citations. Recurring topics across this work include Risk and Safety Analysis (5 papers), Robotic Path Planning Algorithms (4 papers), Graphite, nuclear technology, radiation studies (4 papers), Radiation Shielding Materials Analysis (4 papers), Simulation and Modeling Applications (4 papers), Radiation Therapy and Dosimetry (3 papers), Radiation Detection and Scintillator Technologies (3 papers) and Evacuation and Crowd Dynamics (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (162 citations), Statistics, Probability and Uncertainty (45 citations), Safety, Risk, Reliability and Quality (41 citations), Aerospace Engineering (110 citations) and Radiation (34 citations). Meng-kun Li has collaborated with scholars based in China. Frequent co-authors include Yong-kuo Liu, Chun-li Xie, Nan Chao, Liqun Yang, Fei Xie, Ming Yang, Guohua Wu, Ming Yang, Jun Yang and Ming Yang. Their work appears in journals such as Progress in Nuclear Energy, Annals of Nuclear Energy, Nuclear Engineering and Technology, Nuclear Science and Engineering and Nuclear Engineering and Design.

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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