Guangqing Long
- Numerical Analysis top 5%
- Modeling and Simulation top 2%
- Mechanics of Materials top 10%
- Computational Mechanics top 10%
- Applied Mathematics top 5%
- Co-authors
- Gnaneshwar NelakantiLi‐Bin LiuPayel DasZhongying ChenShan ZhaoLibin LiuHongsong FengZhongdi Cen
- Topics
- Differential Equations and Numerical Methods (15 papers)Advanced Numerical Methods in Computational Mathematics (12 papers)Numerical methods in engineering (12 papers)
- Journals
- Journal of Computational PhysicsApplied Mathematics and ComputationComputers & Mathematics with Applications
- Partner nations
- ChinaIndiaUnited States
In The Last Decade
Guangqing Long
33 papers receiving 314 citations
Peers
Comparison fields: 5 of 44
- Numerical Analysis 207
- Modeling and Simulation 180
- Mechanics of Materials 120
- Computational Mechanics 83
- Applied Mathematics 64
Countries citing papers authored by Guangqing Long
This map shows the geographic impact of Guangqing Long'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 Guangqing Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangqing Long more than expected).
Fields of papers citing papers by Guangqing Long
This network shows the impact of papers produced by Guangqing Long. 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 Guangqing Long. The network helps show where Guangqing Long may publish in the future.
Co-authorship network of co-authors of Guangqing Long
This figure shows the co-authorship network connecting the top 25 collaborators of Guangqing Long. A scholar is included among the top collaborators of Guangqing Long 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 Guangqing Long. Guangqing Long is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | 29 | |
| 5 | 6 | |
| 6 | 9 | |
| 7 | 10 | |
| 8 | 10 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | 1 | |
| 12 | 24 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 7 | |
| 16 | 6 | |
| 17 | 2 | |
| 18 | 5 | |
| 19 | 43 | |
| 20 | 22 |
About Guangqing Long
Guangqing Long is a scholar working on Numerical Analysis, Modeling and Simulation and Computational Mechanics, having authored 34 papers that have together received 331 indexed citations. Recurring topics across this work include Differential Equations and Numerical Methods (15 papers), Advanced Numerical Methods in Computational Mathematics (12 papers) and Numerical methods in engineering (12 papers). The work is most often cited by research in Modeling and Simulation (180 citations), Numerical Analysis (207 citations) and Applied Mathematics (64 citations). Guangqing Long has collaborated with scholars based in China, India and United States. Frequent co-authors include Gnaneshwar Nelakanti, Li‐Bin Liu, Payel Das, Zhongying Chen, Shan Zhao, Libin Liu, Hongsong Feng, Zhongdi Cen, Zaitang Huang and Xiaohua Zhang. Their work appears in journals such as Journal of Computational Physics, Applied Mathematics and Computation and Computers & Mathematics with Applications.
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.