Xu Zhou
Impact in
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing
Papers in
-
- Advanced Graph Neural Networks 7
-
- Graph Theory and Algorithms 8
- Co-authors
- Kenli Li (28 shared papers)Kang Hai Tan (4 shared papers)Bo Yang (4 shared papers)Qiuni Fu (4 shared papers)Keqin Li (12 shared papers)Yunjun Gao (9 shared papers)Cen Chen (3 shared papers)Peng Peng (2 shared papers)
- Journals
- IEEE Transactions on Parallel and Distributed Systems (3 papers)Information Sciences (3 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)Journal of Hazardous Materials (2 papers)Engineering Structures (2 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Xu Zhou
51 papers receiving 503 citations
Peers
Comparison fields: 5 of 83
- Computational Mathematics 7
- Computer Science Applications 49
- Civil and Structural Engineering 142
- Building and Construction 76
- Computer Vision and Pattern Recognition 79
Countries citing papers authored by Xu Zhou
This map shows the geographic impact of Xu Zhou'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 Xu Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xu Zhou more than expected).
Fields of papers citing papers by Xu Zhou
This network shows the impact of papers produced by Xu Zhou. 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 Xu Zhou. The network helps show where Xu Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Xu Zhou, 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 53 | |
| 2 | 2018 | 38 | |
| 3 | 2021 | 30 | |
| 4 | 2017 | 28 | |
| 5 | 2023 | 27 | |
| 6 | 2022 | 26 | |
| 7 | 2021 | 25 | |
| 8 | 2023 | 24 | |
| 9 | 2022 | 21 | |
| 10 | 2014 | 19 | |
| 11 | 2024 | 17 | |
| 12 | 2022 | 17 | |
| 13 | 2018 | 17 | |
| 14 | 2022 | 15 | |
| 15 | 2020 | 12 | |
| 16 | 2020 | 10 | |
| 17 | 2021 | 9 | |
| 18 | 2022 | 9 | |
| 19 | 2023 | 8 | |
| 20 | 2021 | 8 |
About Xu Zhou
Xu Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Civil and Structural Engineering and Computer Science Applications, having authored 57 papers that have together received 507 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (8 papers), Advanced Graph Neural Networks (7 papers), Mobile Crowdsensing and Crowdsourcing (7 papers), Complex Network Analysis Techniques (5 papers), Data Management and Algorithms (4 papers), Structural Load-Bearing Analysis (4 papers), Advanced biosensing and bioanalysis techniques (4 papers) and Structural Response to Dynamic Loads (4 papers). The work is most often cited by research in Computational Mathematics (7 citations), Computer Science Applications (49 citations), Civil and Structural Engineering (142 citations), Building and Construction (76 citations) and Computer Vision and Pattern Recognition (79 citations). Xu Zhou has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Kenli Li, Kang Hai Tan, Bo Yang, Qiuni Fu, Keqin Li, Yunjun Gao, Cen Chen, Peng Peng, Ningbo Zhu and Ming-Feng Lu. Their work appears in journals such as IEEE Transactions on Parallel and Distributed Systems, Information Sciences, IEEE Transactions on Knowledge and Data Engineering, Journal of Hazardous Materials and Engineering Structures.
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.