Siwei Rao
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Domain Adaptation and Few-Shot Learning
- Natural Language Processing Techniques
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- Data Quality and Management
Papers in
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- Topic Modeling 3
- Natural Language Processing Techniques 2
- Advanced Text Analysis Techniques 1
- Advanced Graph Neural Networks 1
- Computational Physics and Python Applications 1
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- Software System Performance and Reliability 1
- Co-authors
- Zhiyuan Liu (1 shared paper)Song Liu (1 shared paper)Huanbo Luan (1 shared paper)Maosong Sun (1 shared paper)Yankai Lin (1 shared paper)Zhen Wang (1 shared paper)Jie Zhang (1 shared paper)Jun Wang (1 shared paper)
- Journals
- Journal of Physics Conference Series (1 paper)International Journal of Engineering Research and (1 paper)
In The Last Decade
Siwei Rao
4 papers receiving 358 citations
Siwei Rao's Hit Papers
Peers
Comparison fields: 5 of 45
- Artificial Intelligence 343
- Management Science and Operations Research 104
- Computational Mathematics 2
- Statistical and Nonlinear Physics 30
- Information Systems 43
Countries citing papers authored by Siwei Rao
This map shows the geographic impact of Siwei Rao'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 Siwei Rao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Siwei Rao more than expected).
Fields of papers citing papers by Siwei Rao
This network shows the impact of papers produced by Siwei Rao. 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 Siwei Rao. The network helps show where Siwei Rao may publish in the future.
Co-authors
The 16 scholars most cited alongside Siwei Rao, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Modeling Relation Paths for Representation Learning of Knowledge Bases Hit paper breakdown → | 2015 | 348 |
| 2 | 2020 | 12 | |
| 3 | TextTN: Probabilistic Encoding of Language on Tensor Network | 2021 | 3 |
| 4 | 2016 | 1 | |
| 5 | 2021 | 0 | |
| 6 | 2020 | 0 |
About Siwei Rao
Siwei Rao is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Computational Mechanics and Atmospheric Science, having authored 6 papers that have together received 364 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers), Advanced Text Analysis Techniques (1 paper), Advanced Graph Neural Networks (1 paper), Combustion and flame dynamics (1 paper), Software System Performance and Reliability (1 paper), Remote Sensing and Land Use (1 paper) and Computational Physics and Python Applications (1 paper). The work is most often cited by research in Artificial Intelligence (343 citations), Management Science and Operations Research (104 citations), Computational Mathematics (2 citations), Statistical and Nonlinear Physics (30 citations) and Information Systems (43 citations). Siwei Rao has collaborated with scholars based in China, Sweden and Mexico. Frequent co-authors include Zhiyuan Liu, Song Liu, Huanbo Luan, Maosong Sun, Yankai Lin, Zhen Wang, Jie Zhang, Jun Wang, Jing Zhang and Peng Zhang. Their work appears in journals such as Journal of Physics Conference Series and International Journal of Engineering Research and.
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.