Bei Wang
Impact in
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- Computer Graphics and Visualization Techniques
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- Data Visualization and Analytics
- Advanced Vision and Imaging
Papers in
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- Topological and Geometric Data Analysis 57
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- Data Visualization and Analytics 35
- Digital Image Processing Techniques 6
- Co-authors
- Valerio Pascucci (16 shared papers)Peer‐Timo Bremer (11 shared papers)Shusen Liu (4 shared papers)Dan Maljovec (8 shared papers)Paul Rosen (12 shared papers)Lin Yan (9 shared papers)Ingrid Hotz (5 shared papers)Mustafa Hajij (5 shared papers)
- Journals
- IEEE Transactions on Visualization and Computer Graphics (18 papers)Computer Graphics Forum (8 papers)Computational Geometry (2 papers)Discrete & Computational Geometry (2 papers)Journal of Lightwave Technology (1 paper)
- Partner nations
- United StatesChinaSweden
In The Last Decade
Bei Wang
94 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 129
- Computer Graphics and Computer-Aided Design 92
- Computer Vision and Pattern Recognition 515
- Biophysics 135
- Computational Theory and Mathematics 368
- Computational Mathematics 6
Countries citing papers authored by Bei Wang
This map shows the geographic impact of Bei Wang'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 Bei Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bei Wang more than expected).
Fields of papers citing papers by Bei Wang
This network shows the impact of papers produced by Bei Wang. 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 Bei Wang. The network helps show where Bei Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Bei Wang, 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 110 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 255 | |
| 2 | 2017 | 67 | |
| 3 | 2021 | 38 | |
| 4 | 2019 | 32 | |
| 5 | 2011 | 29 | |
| 6 | 2018 | 29 | |
| 7 | 2013 | 24 | |
| 8 | 2015 | 23 | |
| 9 | 2018 | 22 | |
| 10 | 2009 | 21 | |
| 11 | 2014 | 21 | |
| 12 | 2020 | 20 | |
| 13 | 2019 | 20 | |
| 14 | 2021 | 18 | |
| 15 | 2015 | 18 | |
| 16 | 2011 | 17 | |
| 17 | 1959 | 15 | |
| 18 | 2012 | 15 | |
| 19 | 2015 | 15 | |
| 20 | 2019 | 12 |
About Bei Wang
Bei Wang is a scholar working on Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Artificial Intelligence, Biophysics and Information Systems, having authored 110 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topological and Geometric Data Analysis (57 papers), Data Visualization and Analytics (35 papers), Cell Image Analysis Techniques (14 papers), Computer Graphics and Visualization Techniques (9 papers), Complex Network Analysis Techniques (8 papers), Data Management and Algorithms (6 papers), Advanced Neuroimaging Techniques and Applications (6 papers) and Digital Image Processing Techniques (6 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (92 citations), Computer Vision and Pattern Recognition (515 citations), Biophysics (135 citations), Computational Theory and Mathematics (368 citations) and Computational Mathematics (6 citations). Bei Wang has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Valerio Pascucci, Peer‐Timo Bremer, Shusen Liu, Dan Maljovec, Paul Rosen, Lin Yan, Ingrid Hotz, Mustafa Hajij, Vivek Srikumar and Jayaraman J. Thiagarajan. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Computational Geometry, Discrete & Computational Geometry and Journal of Lightwave Technology.
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.