Qun Wang
Impact in
- Ecological Modeling top 10%
- Erosion and Abrasive Machining
- Mechanical Engineering top 10%
- Advanced materials and composites
Papers in
-
- Aluminum Alloys Composites Properties 4
-
- Advanced Neural Network Applications 4
- Face and Expression Recognition 4
- Co-authors
- Shiying Zhang (1 shared paper)Yingliang Cheng (2 shared papers)Luoxing Li (1 shared paper)Zhenhua Chen (1 shared paper)Chidambaram Seshadri Ramachandran (8 shared papers)Long Liu (4 shared papers)Tieqiao Chen (4 shared papers)M. Rao (1 shared paper)
- Journals
- Surface and Coatings Technology (4 papers)Ceramics International (2 papers)Applied Sciences (2 papers)New Journal of Chemistry (1 paper)IEEE Access (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Qun Wang
55 papers receiving 651 citations
Peers
Comparison fields: 5 of 94
- Ecological Modeling 36
- Mechanical Engineering 296
- Aerospace Engineering 184
- Mechanics of Materials 124
- Materials Chemistry 194
Countries citing papers authored by Qun Wang
This map shows the geographic impact of Qun 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 Qun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qun Wang more than expected).
Fields of papers citing papers by Qun Wang
This network shows the impact of papers produced by Qun 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 Qun Wang. The network helps show where Qun Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Qun 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 65 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 157 | |
| 2 | 2011 | 80 | |
| 3 | 2021 | 51 | |
| 4 | 2022 | 48 | |
| 5 | 2011 | 33 | |
| 6 | Integrated distributed intelligent systems in manufacturing | 1993 | 30 |
| 7 | 2020 | 21 | |
| 8 | 2022 | 21 | |
| 9 | 2021 | 21 | |
| 10 | 2019 | 17 | |
| 11 | 2022 | 15 | |
| 12 | 2021 | 10 | |
| 13 | 2013 | 10 | |
| 14 | 2022 | 10 | |
| 15 | 2018 | 10 | |
| 16 | 2023 | 8 | |
| 17 | 2022 | 8 | |
| 18 | 2022 | 7 | |
| 19 | 2011 | 6 | |
| 20 | 2015 | 6 |
About Qun Wang
Qun Wang is a scholar working on Mechanical Engineering, Computer Vision and Pattern Recognition, Aerospace Engineering, Artificial Intelligence and Media Technology, having authored 65 papers that have together received 665 indexed citations. Recurring topics across this work include High-Temperature Coating Behaviors (7 papers), Remote-Sensing Image Classification (5 papers), Chemical Synthesis and Analysis (4 papers), Advanced Neural Network Applications (4 papers), Remote Sensing and Land Use (4 papers), Metal and Thin Film Mechanics (4 papers), Aluminum Alloys Composites Properties (4 papers) and Face and Expression Recognition (4 papers). The work is most often cited by research in Ecological Modeling (36 citations), Mechanical Engineering (296 citations), Aerospace Engineering (184 citations), Mechanics of Materials (124 citations) and Materials Chemistry (194 citations). Qun Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Shiying Zhang, Yingliang Cheng, Luoxing Li, Zhenhua Chen, Chidambaram Seshadri Ramachandran, Long Liu, Tieqiao Chen, M. Rao, Tianzeng Huang and Michal Szostak. Their work appears in journals such as Surface and Coatings Technology, Ceramics International, Applied Sciences, New Journal of Chemistry and IEEE Access.
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.