Xiaoliang Wang
- Molecular Biology
- Computer Vision and Pattern Recognition top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Computer Networks and Communications top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Topics
- IoT and Edge/Fog Computing (7 papers)Rock Mechanics and Modeling (7 papers)Advanced Data Storage Technologies (7 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Xiaoliang Wang
96 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 151
- Molecular Biology 212
- Computer Vision and Pattern Recognition 190
- Cardiology and Cardiovascular Medicine 180
- Computer Networks and Communications 174
- Radiology, Nuclear Medicine and Imaging 151
Countries citing papers authored by Xiaoliang Wang
This map shows the geographic impact of Xiaoliang Wang'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 Xiaoliang Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoliang Wang more than expected).
Fields of papers citing papers by Xiaoliang Wang
This network shows the impact of papers produced by Xiaoliang Wang. 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 Xiaoliang Wang. The network helps show where Xiaoliang Wang may publish in the future.
Co-authorship network of co-authors of Xiaoliang Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoliang Wang. A scholar is included among the top collaborators of Xiaoliang Wang 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 Xiaoliang Wang. Xiaoliang Wang 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 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 8 | |
| 10 | 4 | |
| 11 | 0 | |
| 12 | 3 | |
| 13 | 13 | |
| 14 | 2 | |
| 15 | 5 | |
| 16 | 7 | |
| 17 | Strategies for the development of drugs targeting novel coronavirus 2019-nCoV | 4 |
| 18 | 106 | |
| 19 | SAR image segmentation using level set evolution without prior information | 1 |
| 20 | NONLINEAR ANALYTICAL MODELS, METHODS AND EXAMPLES FOR CONCRETE STRUCTURES SUBJECT TO EARTHQUAKE LOADING | 12 |
About Xiaoliang Wang
Xiaoliang Wang is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Neurology, having authored 105 papers that have together received 1.3k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (7 papers), Rock Mechanics and Modeling (7 papers) and Advanced Data Storage Technologies (7 papers). The work is most often cited by research in Health Information Management (57 citations), Computer Vision and Pattern Recognition (190 citations) and Ophthalmology (77 citations). Xiaoliang Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Zhanpeng Jin, Yongjin Lu, Wei-Bang Chen, Yujuan Wang, Bingwei Liu, Qiong Gui, Houbing Song, Wei Wei, Yu Chen and Ke Xu. Their work appears in journals such as Circulation, PLoS ONE and Applied and Environmental Microbiology.
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.