Yichen Song
Impact in
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- Advanced Graph Neural Networks
- Topic Modeling
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- Fire Detection and Safety Systems
Papers in
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- Advanced Graph Neural Networks 7
- Topic Modeling 7
- Advanced Text Analysis Techniques 3
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- Rough Sets and Fuzzy Logic 4
- Co-authors
- Aiping Li (9 shared papers)Yan Jia (4 shared papers)Rong Jiang (2 shared papers)Lianbo Zeng (5 shared papers)Zhe Mao (4 shared papers)Guoping Liu (1 shared paper)Xinggao Liu (5 shared papers)Zijian Tian (1 shared paper)
- Journals
- IEEE Internet of Things Journal (2 papers)Petroleum Exploration and Development (1 paper)Frontiers in Neurorobotics (1 paper)Journal of Petroleum Science and Engineering (1 paper)World Wide Web (1 paper)
- Partner nations
- ChinaPortugalUnited Kingdom
In The Last Decade
Yichen Song
28 papers receiving 263 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 83
- Safety, Risk, Reliability and Quality 20
- Management Science and Operations Research 27
- Geology 11
- Mechanics of Materials 45
Countries citing papers authored by Yichen Song
This map shows the geographic impact of Yichen 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 Yichen Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yichen Song more than expected).
Fields of papers citing papers by Yichen Song
This network shows the impact of papers produced by Yichen 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 Yichen Song. The network helps show where Yichen Song may publish in the future.
Co-authors
The 25 scholars most cited alongside Yichen 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 67 | |
| 2 | 2023 | 45 | |
| 3 | 2023 | 28 | |
| 4 | 2019 | 19 | |
| 5 | 2021 | 12 | |
| 6 | 2025 | 10 | |
| 7 | 2022 | 10 | |
| 8 | 2022 | 8 | |
| 9 | 2025 | 8 | |
| 10 | 2019 | 6 | |
| 11 | 2020 | 6 | |
| 12 | 2021 | 6 | |
| 13 | 2021 | 6 | |
| 14 | 2024 | 5 | |
| 15 | 2024 | 4 | |
| 16 | 2023 | 4 | |
| 17 | 2025 | 3 | |
| 18 | 2023 | 3 | |
| 19 | 2023 | 3 | |
| 20 | 2025 | 3 |
About Yichen Song
Yichen Song is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Statistical and Nonlinear Physics, Mechanics of Materials and Geophysics, having authored 32 papers that have together received 270 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (7 papers), Topic Modeling (7 papers), Hydrocarbon exploration and reservoir analysis (5 papers), Rough Sets and Fuzzy Logic (4 papers), Complex Network Analysis Techniques (4 papers), Seismic Imaging and Inversion Techniques (3 papers), Advanced Text Analysis Techniques (3 papers) and Viral Infectious Diseases and Gene Expression in Insects (2 papers). The work is most often cited by research in Artificial Intelligence (83 citations), Safety, Risk, Reliability and Quality (20 citations), Management Science and Operations Research (27 citations), Geology (11 citations) and Mechanics of Materials (45 citations). Yichen Song has collaborated with scholars based in China, Portugal and United Kingdom. Frequent co-authors include Aiping Li, Yan Jia, Rong Jiang, Lianbo Zeng, Zhe Mao, Guoping Liu, Xinggao Liu, Zijian Tian, Guangye Li and Ye Wang. Their work appears in journals such as IEEE Internet of Things Journal, Petroleum Exploration and Development, Frontiers in Neurorobotics, Journal of Petroleum Science and Engineering and World Wide Web.
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.