Sanling Song
- Safety, Risk, Reliability and Quality top 0.5%
- Statistics, Probability and Uncertainty top 0.5%
- Software top 2%
- Statistics and Probability top 2%
- Control and Systems Engineering top 10%
- Co-authors
- David W. CoitQianmei FengHao PengLei XiaoXiaohong ChenNooshin YousefiQiuliang WangYan Liang
- Topics
- Reliability and Maintenance Optimization (8 papers)Software Reliability and Analysis Research (6 papers)Superconducting Materials and Applications (5 papers)
- Journals
- Reliability Engineering & System SafetyThe International Journal of Advanced Manufacturing TechnologyComputers & Industrial Engineering
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Sanling Song
17 papers receiving 778 citations
Peers
Comparison fields: 5 of 61
- Safety, Risk, Reliability and Quality 548
- Statistics, Probability and Uncertainty 294
- Software 222
- Statistics and Probability 157
- Control and Systems Engineering 95
Countries citing papers authored by Sanling Song
This map shows the geographic impact of Sanling Song'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 Sanling Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanling Song more than expected).
Fields of papers citing papers by Sanling Song
This network shows the impact of papers produced by Sanling Song. 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 Sanling Song. The network helps show where Sanling Song may publish in the future.
Co-authorship network of co-authors of Sanling Song
This figure shows the co-authorship network connecting the top 25 collaborators of Sanling Song. A scholar is included among the top collaborators of Sanling Song 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 Sanling Song. Sanling Song is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 40 | |
| 3 | 50 | |
| 4 | 47 | |
| 5 | 92 | |
| 6 | 11 | |
| 7 | 135 | |
| 8 | 97 | |
| 9 | 199 | |
| 10 | 7 | |
| 11 | 3 | |
| 12 | 17 | |
| 13 | 22 | |
| 14 | 6 | |
| 15 | 16 | |
| 16 | 44 | |
| 17 | 6 |
About Sanling Song
Sanling Song is a scholar working on Software, Safety, Risk, Reliability and Quality and Medical Laboratory Technology, having authored 17 papers that have together received 803 indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (8 papers), Software Reliability and Analysis Research (6 papers) and Superconducting Materials and Applications (5 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (548 citations), Software (222 citations) and Statistics, Probability and Uncertainty (294 citations). Sanling Song has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include David W. Coit, Qianmei Feng, Hao Peng, Lei Xiao, Xiaohong Chen, Nooshin Yousefi, Qiuliang Wang, Yan Liang, B. Zhao and Wang Hong-gang. Their work appears in journals such as Reliability Engineering & System Safety, The International Journal of Advanced Manufacturing Technology and Computers & Industrial 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.