Song Liu
- Biomedical Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 5%
- Mechanical Engineering top 10%
- Aerospace Engineering top 10%
- Co-authors
- De XuYoufu LiDengpeng XingDapeng ZhangZhengtao ZhangZhongyuan WangShengsheng QianHaoqi Fan
- Topics
- Microfluidic and Bio-sensing Technologies (16 papers)Acoustic Wave Phenomena Research (11 papers)Robot Manipulation and Learning (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionHuman-Computer InteractionControl and Systems Engineering
- Journals
- SHILAP Revista de lepidopterologíaApplied Physics LettersJournal of Applied Physics
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Song Liu
103 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 120
- Biomedical Engineering 519
- Computer Vision and Pattern Recognition 299
- Control and Systems Engineering 281
- Mechanical Engineering 172
- Aerospace Engineering 133
Countries citing papers authored by Song Liu
This map shows the geographic impact of Song Liu'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 Song Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Liu more than expected).
Fields of papers citing papers by Song Liu
This network shows the impact of papers produced by Song Liu. 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 Song Liu. The network helps show where Song Liu may publish in the future.
Co-authorship network of co-authors of Song Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Song Liu. A scholar is included among the top collaborators of Song Liu 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 Song Liu. Song Liu 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 | 0 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 6 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 6 | |
| 10 | 2 | |
| 11 | 0 | |
| 12 | 4 | |
| 13 | 2 | |
| 14 | 5 | |
| 15 | 17 | |
| 16 | 13 | |
| 17 | 12 | |
| 18 | 26 | |
| 19 | 3 | |
| 20 | 12 |
About Song Liu
Song Liu is a scholar working on Structural Biology, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 128 papers that have together received 1.3k indexed citations. Recurring topics across this work include Microfluidic and Bio-sensing Technologies (16 papers), Acoustic Wave Phenomena Research (11 papers) and Robot Manipulation and Learning (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (299 citations), Human-Computer Interaction (70 citations) and Control and Systems Engineering (281 citations). Song Liu has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include De Xu, Youfu Li, Dengpeng Xing, Dapeng Zhang, Zhengtao Zhang, Zhongyuan Wang, Shengsheng Qian, Haoqi Fan, Yiru Chen and Wenkui Ding. Their work appears in journals such as SHILAP Revista de lepidopterología, Applied Physics Letters and Journal of Applied Physics.
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.