Senwei Liang
Impact in
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- Model Reduction and Neural Networks
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- Human Mobility and Location-Based Analysis
Papers in
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- Neural Networks and Applications 4
- Domain Adaptation and Few-Shot Learning 4
- Quantum Information and Cryptography 2
- Quantum Computing Algorithms and Architecture 2
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- Model Reduction and Neural Networks 5
- Advanced Thermodynamics and Statistical Mechanics 2
- Co-authors
- Haizhao Yang (7 shared papers)John Harlim (3 shared papers)Takahiro Yabe (1 shared paper)Satish V. Ukkusuri (1 shared paper)Jianzhu Ma (1 shared paper)Nan Jiang (1 shared paper)Chao Yang (6 shared papers)Yuehaw Khoo (1 shared paper)
- Journals
- Machine Learning Science and Technology (2 papers)Journal of Computational Physics (1 paper)Neurocomputing (1 paper)Physical Review Research (1 paper)Applied and Computational Harmonic Analysis (1 paper)
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Senwei Liang
14 papers receiving 221 citations
Peers
Comparison fields: 5 of 62
- Statistical and Nonlinear Physics 60
- Transportation 23
- Artificial Intelligence 82
- Computer Vision and Pattern Recognition 49
- Building and Construction 29
Countries citing papers authored by Senwei Liang
This map shows the geographic impact of Senwei Liang'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 Senwei Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Senwei Liang more than expected).
Fields of papers citing papers by Senwei Liang
This network shows the impact of papers produced by Senwei Liang. 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 Senwei Liang. The network helps show where Senwei Liang may publish in the future.
Co-authors
The 17 scholars most cited alongside Senwei Liang, 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 | 2022 | 72 | |
| 2 | 2020 | 46 | |
| 3 | 2020 | 32 | |
| 4 | 2020 | 16 | |
| 5 | 2020 | 12 | |
| 6 | 2023 | 9 | |
| 7 | 2023 | 7 | |
| 8 | 2024 | 7 | |
| 9 | 2023 | 6 | |
| 10 | 2023 | 6 | |
| 11 | 2024 | 4 | |
| 12 | 2024 | 4 | |
| 13 | 2024 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2025 | 0 |
About Senwei Liang
Senwei Liang is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics and Materials Chemistry, having authored 15 papers that have together received 224 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (5 papers), Neural Networks and Applications (4 papers), Advanced Neural Network Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Advanced Thermodynamics and Statistical Mechanics (2 papers), Quantum Information and Cryptography (2 papers), Quantum many-body systems (2 papers) and Quantum Computing Algorithms and Architecture (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (60 citations), Transportation (23 citations), Artificial Intelligence (82 citations), Computer Vision and Pattern Recognition (49 citations) and Building and Construction (29 citations). Senwei Liang has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Haizhao Yang, John Harlim, Takahiro Yabe, Satish V. Ukkusuri, Jianzhu Ma, Nan Jiang, Chao Yang, Yuehaw Khoo, Xiaosong Li and Yin Jia. Their work appears in journals such as Machine Learning Science and Technology, Journal of Computational Physics, Neurocomputing, Physical Review Research and Applied and Computational Harmonic Analysis.
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.