Yuqi Song
- Materials Chemistry top 10%
- Electrical and Electronic Engineering
- Computational Theory and Mathematics top 5%
- Biomedical Engineering
- Artificial Intelligence
- Co-authors
- Jianjun HuYong ZhaoSteph-Yves LouisEdirisuriya M. Dilanga SiriwardaneAlireza NasiriFei LiuXiran WangRongzhi Dong
- Topics
- Machine Learning in Materials Science (13 papers)X-ray Diffraction in Crystallography (5 papers)Recommender Systems and Techniques (5 papers)
- Cited by
- Materials ChemistryComputational Theory and MathematicsElectronic, Optical and Magnetic Materials
- Journals
- SHILAP Revista de lepidopterologíaRemote Sensing of EnvironmentACS Applied Materials & Interfaces
- Partner nations
- ChinaUnited StatesSri Lanka
In The Last Decade
Yuqi Song
47 papers receiving 762 citations
Peers
Comparison fields: 5 of 134
- Materials Chemistry 423
- Electrical and Electronic Engineering 131
- Computational Theory and Mathematics 112
- Biomedical Engineering 80
- Artificial Intelligence 73
Countries citing papers authored by Yuqi Song
This map shows the geographic impact of Yuqi 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 Yuqi Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuqi Song more than expected).
Fields of papers citing papers by Yuqi Song
This network shows the impact of papers produced by Yuqi 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 Yuqi Song. The network helps show where Yuqi Song may publish in the future.
Co-authorship network of co-authors of Yuqi Song
This figure shows the co-authorship network connecting the top 25 collaborators of Yuqi Song. A scholar is included among the top collaborators of Yuqi 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 Yuqi Song. Yuqi 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 | 0 | |
| 2 | 0 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 5 | |
| 9 | 17 | |
| 10 | 1 | |
| 11 | 24 | |
| 12 | 10 | |
| 13 | 14 | |
| 14 | 10 | |
| 15 | 14 | |
| 16 | 6 | |
| 17 | 5 | |
| 18 | 65 | |
| 19 | 16 | |
| 20 | 160 |
About Yuqi Song
Yuqi Song is a scholar working on Equine, Software and Information Systems, having authored 54 papers that have together received 780 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (13 papers), X-ray Diffraction in Crystallography (5 papers) and Recommender Systems and Techniques (5 papers). The work is most often cited by research in Materials Chemistry (423 citations), Computational Theory and Mathematics (112 citations) and Electronic, Optical and Magnetic Materials (69 citations). Yuqi Song has collaborated with scholars based in China, United States and Sri Lanka. Frequent co-authors include Jianjun Hu, Yong Zhao, Steph-Yves Louis, Edirisuriya M. Dilanga Siriwardane, Alireza Nasiri, Fei Liu, Xiran Wang, Rongzhi Dong, Haifeng Yang and Sadman Sadeed Omee. Their work appears in journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and ACS Applied Materials & Interfaces.
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.