Jun Song
Impact in
- Genetics top 10%
- Mesenchymal stem cell research
- Automotive Engineering top 10%
- Additive Manufacturing and 3D Printing Technologies
Papers in
-
- Bone Tissue Engineering Materials 2
- Microfluidic and Bio-sensing Technologies 2
-
- Underwater Acoustics Research 4
- Oceanographic and Atmospheric Processes 3
- Co-authors
- Lei Sun (2 shared papers)Li Chen (2 shared papers)Weikai Hou (2 shared papers)Shuai Ma (2 shared papers)Rossitza Setchi (2 shared papers)Qian Tang (2 shared papers)Qixiang Feng (2 shared papers)Y. Y. Tse (1 shared paper)
- Journals
- The Journal of the Acoustical Society of America (4 papers)Scientific Reports (2 papers)Cell Reports (2 papers)Frontiers in Marine Science (1 paper)RSC Advances (1 paper)
- Partner nations
- ChinaSouth KoreaCanada
In The Last Decade
Jun Song
32 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 116
- Genetics 143
- Automotive Engineering 121
- Surgery 278
- Endocrine and Autonomic Systems 31
- Cellular and Molecular Neuroscience 84
Countries citing papers authored by Jun Song
This map shows the geographic impact of Jun 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 Jun Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Song more than expected).
Fields of papers citing papers by Jun Song
This network shows the impact of papers produced by Jun 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 Jun Song. The network helps show where Jun Song may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Song, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 191 | |
| 2 | 2007 | 165 | |
| 3 | 2020 | 93 | |
| 4 | 2013 | 80 | |
| 5 | 2018 | 75 | |
| 6 | 2008 | 60 | |
| 7 | 2013 | 53 | |
| 8 | 2007 | 53 | |
| 9 | 2020 | 32 | |
| 10 | 2021 | 23 | |
| 11 | 2020 | 22 | |
| 12 | 2022 | 22 | |
| 13 | 2021 | 18 | |
| 14 | 2020 | 17 | |
| 15 | 2021 | 14 | |
| 16 | 2019 | 14 | |
| 17 | 2016 | 14 | |
| 18 | 2018 | 13 | |
| 19 | 2018 | 11 | |
| 20 | 2019 | 8 |
About Jun Song
Jun Song is a scholar working on Biomedical Engineering, Oceanography, Cellular and Molecular Neuroscience, Cognitive Neuroscience and Biophysics, having authored 35 papers that have together received 1.0k indexed citations. Recurring topics across this work include Underwater Acoustics Research (4 papers), Oceanographic and Atmospheric Processes (3 papers), Cell Image Analysis Techniques (3 papers), Neuroscience and Neural Engineering (2 papers), Mesenchymal stem cell research (2 papers), Bacterial Identification and Susceptibility Testing (2 papers), Bone Tissue Engineering Materials (2 papers) and Microfluidic and Bio-sensing Technologies (2 papers). The work is most often cited by research in Genetics (143 citations), Automotive Engineering (121 citations), Surgery (278 citations), Endocrine and Autonomic Systems (31 citations) and Cellular and Molecular Neuroscience (84 citations). Jun Song has collaborated with scholars based in China, South Korea and Canada. Frequent co-authors include Lei Sun, Li Chen, Weikai Hou, Shuai Ma, Rossitza Setchi, Qian Tang, Qixiang Feng, Y. Y. Tse, Yang Liu and Xiaoxiao Han. Their work appears in journals such as The Journal of the Acoustical Society of America, Scientific Reports, Cell Reports, Frontiers in Marine Science and RSC Advances.
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.