Xinyuan Song
- Statistics and Probability top 0.2%
- Artificial Intelligence top 2%
- Management Science and Operations Research top 2%
- Plant Science top 10%
- Economics and Econometrics top 5%
- Co-authors
- Sik‐Yum LeeWenyang ZhangLiuquan SunJianbing LiRonald W. ThringXiangnan FengXuan HuZhang Ju
- Topics
- Statistical Methods and Bayesian Inference (54 papers)Statistical Methods and Inference (53 papers)Bayesian Methods and Mixture Models (28 papers)
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchArtificial Intelligence
- Journals
- Journal of the American Statistical AssociationPLoS ONEIEEE Transactions on Automatic Control
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Xinyuan Song
132 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 184
- Statistics and Probability 1.3k
- Artificial Intelligence 607
- Management Science and Operations Research 265
- Plant Science 224
- Economics and Econometrics 219
Countries citing papers authored by Xinyuan Song
This map shows the geographic impact of Xinyuan 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 Xinyuan Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xinyuan Song more than expected).
Fields of papers citing papers by Xinyuan Song
This network shows the impact of papers produced by Xinyuan 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 Xinyuan Song. The network helps show where Xinyuan Song may publish in the future.
Co-authorship network of co-authors of Xinyuan Song
This figure shows the co-authorship network connecting the top 25 collaborators of Xinyuan Song. A scholar is included among the top collaborators of Xinyuan 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 Xinyuan Song. Xinyuan 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 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 21 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 6 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 35 | |
| 13 | 3 | |
| 14 | 14 | |
| 15 | 3 | |
| 16 | 4 | |
| 17 | 16 | |
| 18 | 27 | |
| 19 | 4 | |
| 20 | 208 |
About Xinyuan Song
Xinyuan Song is a scholar working on Statistics and Probability, Artificial Intelligence and Finance, having authored 144 papers that have together received 2.8k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (54 papers), Statistical Methods and Inference (53 papers) and Bayesian Methods and Mixture Models (28 papers). The work is most often cited by research in Statistics and Probability (1.3k citations), Management Science and Operations Research (265 citations) and Artificial Intelligence (607 citations). Xinyuan Song has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Sik‐Yum Lee, Wenyang Zhang, Liuquan Sun, Jianbing Li, Ronald W. Thring, Xiangnan Feng, Xuan Hu, Zhang Ju, Zhaohua Lu and Jingheng Cai. Their work appears in journals such as Journal of the American Statistical Association, PLoS ONE and IEEE Transactions on Automatic Control.
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.