Shuxin Yang
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Co-authors
- Zhendong WangAta Jahangir MoshayediDahai LiAmir Sohail KhanJie CaoGuixiang ZhuYouquan WangSammy Chan
- Topics
- Recommender Systems and Techniques (6 papers)Advanced Neural Network Applications (6 papers)Energy Efficient Wireless Sensor Networks (6 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Shuxin Yang
55 papers receiving 468 citations
Peers
Comparison fields: 5 of 93
- Artificial Intelligence 186
- Computer Networks and Communications 140
- Information Systems 97
- Computer Vision and Pattern Recognition 94
- Electrical and Electronic Engineering 60
Countries citing papers authored by Shuxin Yang
This map shows the geographic impact of Shuxin Yang'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 Shuxin Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuxin Yang more than expected).
Fields of papers citing papers by Shuxin Yang
This network shows the impact of papers produced by Shuxin Yang. 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 Shuxin Yang. The network helps show where Shuxin Yang may publish in the future.
Co-authorship network of co-authors of Shuxin Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Shuxin Yang. A scholar is included among the top collaborators of Shuxin Yang 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 Shuxin Yang. Shuxin Yang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 2 | |
| 9 | 6 | |
| 10 | 7 | |
| 11 | 7 | |
| 12 | 7 | |
| 13 | 5 | |
| 14 | 27 | |
| 15 | 22 | |
| 16 | 14 | |
| 17 | 18 | |
| 18 | 14 | |
| 19 | Research of flexible dynamic change in workflow process management system for business process | 0 |
| 20 | 3 |
About Shuxin Yang
Shuxin Yang is a scholar working on Computer Networks and Communications, Artificial Intelligence and Statistics and Probability, having authored 63 papers that have together received 482 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (6 papers), Advanced Neural Network Applications (6 papers) and Energy Efficient Wireless Sensor Networks (6 papers). The work is most often cited by research in Computer Networks and Communications (140 citations), Artificial Intelligence (186 citations) and Health Informatics (7 citations). Shuxin Yang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Zhendong Wang, Ata Jahangir Moshayedi, Dahai Li, Amir Sohail Khan, Jie Cao, Guixiang Zhu, Youquan Wang, Sammy Chan, Jingfei Li and Daojing He. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and IEEE Journal of Solid-State Circuits.
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.