Meng-kun Li

20 papers receiving 290 citations

Peers

Meng-kun Li
Comparison fields: 5 of 47
  • Computer Vision and Pattern Recognition 168
  • Statistics, Probability and Uncertainty 39
  • Aerospace Engineering 112
  • Safety, Risk, Reliability and Quality 39
  • Radiation 34
Replace Chun-li Xie with:
Chun-li Xie China
Nan Chao China
Alexandru Stancu United Kingdom
Jianping Ma China
Jingchao Peng China
Qi Dong China
Jianbo Hu China
Jae-Woo Lee South Korea
Linyu Lin United States
Li Fu China
Meng-kun Li relative to Chun-li Xie China Chun-li Xie's profile →
Citations per field
00.5×1.6×
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 18 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 201448
2 201548
3 201531
4 201630
5 201630
6 201816
7 201913
8 201913
9 201811
10 20169
11 20188
12 20197
13 20216
14 20196
15 20206
16 20215
17 20195
18 20234
19 20214
20 20183

About Meng-kun Li

Meng-kun Li is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Statistics, Probability and Uncertainty, Materials Chemistry and Radiation, having authored 21 papers that have together received 303 indexed citations. Recurring topics across this work include Risk and Safety Analysis (5 papers), Robotic Path Planning Algorithms (5 papers), Graphite, nuclear technology, radiation studies (4 papers), Simulation and Modeling Applications (4 papers), Radiation Shielding Materials Analysis (4 papers), Radiation Detection and Scintillator Technologies (3 papers), Radiation Therapy and Dosimetry (3 papers) and Robotics and Sensor-Based Localization (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (168 citations), Statistics, Probability and Uncertainty (39 citations), Aerospace Engineering (112 citations), Safety, Risk, Reliability and Quality (39 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, Minjun Peng, Nan Chao, Liqun Yang, Fei Xie, Ming Yang, Guohua Wu, Ming Yang and Ming Yang. Their work appears in journals such as Progress in Nuclear Energy, Annals of Nuclear Energy, Nuclear Engineering and Technology, Journal of Radiological Protection and Arabian Journal for Science and Engineering.

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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