Yipu Zhang
Impact in
- Computational Mathematics top 10%
- Tensor decomposition and applications
- Cognitive Neuroscience top 10%
- Functional Brain Connectivity Studies
Papers in
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- Tensor decomposition and applications 3
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- Functional Brain Connectivity Studies 6
- Co-authors
- Zhenbo Yu (1 shared paper)Huagang Liang (1 shared paper)Vince D. Calhoun (5 shared papers)Yu‐Ping Wang (6 shared papers)Tony W. Wilson (3 shared papers)Julia M. Stephen (3 shared papers)Li Xiao (2 shared papers)Peyman Hosseinzadeh Kassani (1 shared paper)
- Journals
- IEEE Journal of Biomedical and Health Informatics (2 papers)IEEE Transactions on Computational Biology and Bioinformatics (1 paper)Neuropharmacology (1 paper)IEEE Access (1 paper)The Journal of Supercritical Fluids (1 paper)
- Partner nations
- ChinaUnited StatesBangladesh
In The Last Decade
Yipu Zhang
14 papers receiving 285 citations
Peers
Comparison fields: 5 of 49
- Computational Mathematics 9
- Cognitive Neuroscience 92
- Experimental and Cognitive Psychology 60
- Computer Vision and Pattern Recognition 36
- Automotive Engineering 12
Countries citing papers authored by Yipu Zhang
This map shows the geographic impact of Yipu Zhang'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 Yipu Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yipu Zhang more than expected).
Fields of papers citing papers by Yipu Zhang
This network shows the impact of papers produced by Yipu Zhang. 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 Yipu Zhang. The network helps show where Yipu Zhang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yipu Zhang, 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 | 2019 | 84 | |
| 2 | 2019 | 78 | |
| 3 | 2020 | 25 | |
| 4 | 2020 | 18 | |
| 5 | 2019 | 17 | |
| 6 | 2024 | 16 | |
| 7 | 2023 | 15 | |
| 8 | 2020 | 13 | |
| 9 | 2023 | 8 | |
| 10 | 2024 | 8 | |
| 11 | 2020 | 4 | |
| 12 | 2020 | 3 | |
| 13 | 2022 | 1 | |
| 14 | 2024 | 1 | |
| 15 | 2022 | 0 |
About Yipu Zhang
Yipu Zhang is a scholar working on Computational Mathematics, Cognitive Neuroscience, Automotive Engineering, Behavioral Neuroscience and Computer Graphics and Computer-Aided Design, having authored 15 papers that have together received 291 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (6 papers), Tensor decomposition and applications (3 papers), Advanced Battery Technologies Research (2 papers), Schizophrenia research and treatment (1 paper), Sulfur Compounds in Biology (1 paper), Digital Media and Visual Art (1 paper), Advanced Combustion Engine Technologies (1 paper) and Emotion and Mood Recognition (1 paper). The work is most often cited by research in Computational Mathematics (9 citations), Cognitive Neuroscience (92 citations), Experimental and Cognitive Psychology (60 citations), Computer Vision and Pattern Recognition (36 citations) and Automotive Engineering (12 citations). Yipu Zhang has collaborated with scholars based in China, United States and Bangladesh. Frequent co-authors include Zhenbo Yu, Huagang Liang, Vince D. Calhoun, Yu‐Ping Wang, Tony W. Wilson, Julia M. Stephen, Li Xiao, Peyman Hosseinzadeh Kassani, Yuntong Bai and Junqi Wang. Their work appears in journals such as IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Computational Biology and Bioinformatics, Neuropharmacology, IEEE Access and The Journal of Supercritical Fluids.
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.