Weihong Qian
- Computational Mathematics top 2%
-
- Data Visualization and Analytics 8
- Video Analysis and Summarization 4
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- Complex Network Analysis Techniques 4
- Artificial Intelligence top 5%
- Advanced Text Analysis Techniques 5
- Topic Modeling 3
- Text and Document Classification Technologies 2
- General Social Sciences top 2%
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- Radio Frequency Integrated Circuit Design 2
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- Topological and Geometric Data Analysis 2
- Cited by
- Computational MathematicsComputer Vision and Pattern RecognitionStatistical and Nonlinear Physics
- Journals
- Visual Informatics (1 paper)ACM Transactions on Intelligent Systems and Technology (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Weihong Qian
16 papers receiving 538 citations
Peers
Comparison fields: 5 of 69
- Computational Mathematics 43
- Computer Vision and Pattern Recognition 312
- Statistical and Nonlinear Physics 117
- Artificial Intelligence 295
- General Social Sciences 22
Countries citing papers authored by Weihong Qian
This map shows the geographic impact of Weihong Qian'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 Weihong Qian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weihong Qian more than expected).
Fields of papers citing papers by Weihong Qian
This network shows the impact of papers produced by Weihong Qian. 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 Weihong Qian. The network helps show where Weihong Qian may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Weihong Qian, 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 | 1 | |
| 2 | 2021 | 9 | |
| 3 | 2020 | 7 | |
| 4 | 2013 | 1 | |
| 5 | 2013 | 4 | |
| 6 | 2013 | 11 | |
| 7 | 2012 | 112 | |
| 8 | 2012 | 19 | |
| 9 | 2012 | 15 | |
| 10 | 2010 | 29 | |
| 11 | 2010 | 150 | |
| 12 | 2009 | 64 | |
| 13 | 2009 | 58 | |
| 14 | 2009 | 27 | |
| 15 | 2009 | 52 | |
| 16 | 2006 | 2 |
About Weihong Qian
Weihong Qian is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Artificial Intelligence and Computational Theory and Mathematics, having authored 16 papers that have together received 561 indexed citations. Recurring topics across this work include Data Visualization and Analytics (8 papers), Advanced Text Analysis Techniques (5 papers), Complex Network Analysis Techniques (4 papers), Video Analysis and Summarization (4 papers), Topic Modeling (3 papers), Radio Frequency Integrated Circuit Design (2 papers), Topological and Geometric Data Analysis (2 papers) and Text and Document Classification Technologies (2 papers). The work is most often cited by research in Computational Mathematics (43 citations), Computer Vision and Pattern Recognition (312 citations), Statistical and Nonlinear Physics (117 citations), Artificial Intelligence (295 citations) and General Social Sciences (22 citations). Weihong Qian has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Shi‐Xia Liu, Shimei Pan, Michelle X. Zhou, Yangqiu Song, Weijia Cai, Lei Shi, Furu Wei, Li Tan, Qiang Zhang and Nan Cao. Their work appears in journals such as Visual Informatics, ACM Transactions on Intelligent Systems and Technology, IEEE Transactions on Knowledge and Data Engineering, Journal of Visualization and Rare & Special e-Zone (The Hong Kong University of Science and 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.