Kangshun Li
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 1%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Molecular Biology
- Co-authors
- Zhiping TanZhiyi LinFeng WangJun YangXiao‐Liang ShenHeng ZhangHongshuai ZhuAori Qileng
- Topics
- Metaheuristic Optimization Algorithms Research (48 papers)Evolutionary Algorithms and Applications (35 papers)Advanced Multi-Objective Optimization Algorithms (26 papers)
- Cited by
- Computational Theory and MathematicsArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEAnalytical Chemistry
In The Last Decade
Kangshun Li
114 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Artificial Intelligence 760
- Computational Theory and Mathematics 402
- Computer Vision and Pattern Recognition 290
- Electrical and Electronic Engineering 267
- Molecular Biology 203
Countries citing papers authored by Kangshun Li
This map shows the geographic impact of Kangshun 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 Kangshun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kangshun Li more than expected).
Fields of papers citing papers by Kangshun Li
This network shows the impact of papers produced by Kangshun 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 Kangshun Li. The network helps show where Kangshun Li may publish in the future.
Co-authorship network of co-authors of Kangshun Li
This figure shows the co-authorship network connecting the top 25 collaborators of Kangshun Li. A scholar is included among the top collaborators of Kangshun Li 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 Kangshun Li. Kangshun Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 4 | |
| 8 | 16 | |
| 9 | 13 | |
| 10 | 4 | |
| 11 | 26 | |
| 12 | 7 | |
| 13 | 6 | |
| 14 | 4 | |
| 15 | 21 | |
| 16 | 3 | |
| 17 | 9 | |
| 18 | 4 | |
| 19 | Evolutionary Algorithm for Solving Complex Problem Based on Queen-Bee Mating | 1 |
| 20 | A NEW ALGORITHM OF EVOLVING ARTIFICIAL NEURAL NETWORKS VIA GENE EXPRESSION PROGRAMMING | 1 |
About Kangshun Li
Kangshun Li is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 128 papers that have together received 1.8k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (48 papers), Evolutionary Algorithms and Applications (35 papers) and Advanced Multi-Objective Optimization Algorithms (26 papers). The work is most often cited by research in Computational Theory and Mathematics (402 citations), Artificial Intelligence (760 citations) and Computer Vision and Pattern Recognition (290 citations). Kangshun Li has collaborated with scholars based in China, Canada and Hong Kong. Frequent co-authors include Zhiping Tan, Zhiyi Lin, Feng Wang, Jun Yang, Xiao‐Liang Shen, Heng Zhang, Hongshuai Zhu, Aori Qileng, Yue Cai and Yingju Liu. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Analytical Chemistry.
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.