Sheng-Ming Wang
Impact in
- Human-Computer Interaction top 10%
- Hand Gesture Recognition Systems
Papers in
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- Augmented Reality Applications 3
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- Mitochondrial Function and Pathology 3
- Co-authors
- Yayun Wang (3 shared papers)Yanling Yang (3 shared papers)Chun‐Qiu Dai (1 shared paper)Jiaqi Wang (1 shared paper)Tingting Luo (1 shared paper)Fangfang Li (1 shared paper)Zengzhao Chen (2 shared papers)An‐Wu Xu (1 shared paper)
In The Last Decade
Sheng-Ming Wang
44 papers receiving 354 citations
Peers
Comparison fields: 5 of 140
- Human-Computer Interaction 26
- Media Technology 20
- Cancer Research 33
- Biophysics 11
- Computer Vision and Pattern Recognition 35
Countries citing papers authored by Sheng-Ming Wang
This map shows the geographic impact of Sheng-Ming 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 Sheng-Ming Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sheng-Ming Wang more than expected).
Fields of papers citing papers by Sheng-Ming Wang
This network shows the impact of papers produced by Sheng-Ming 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 Sheng-Ming Wang. The network helps show where Sheng-Ming Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Sheng-Ming 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 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 80 | |
| 2 | 2010 | 42 | |
| 3 | 2018 | 26 | |
| 4 | 2020 | 25 | |
| 5 | 2023 | 18 | |
| 6 | 2016 | 14 | |
| 7 | 2024 | 14 | |
| 8 | 2024 | 12 | |
| 9 | 2018 | 11 | |
| 10 | 2021 | 10 | |
| 11 | 2018 | 10 | |
| 12 | 2023 | 7 | |
| 13 | 2017 | 7 | |
| 14 | 2023 | 6 | |
| 15 | 2020 | 6 | |
| 16 | 2024 | 5 | |
| 17 | 2023 | 5 | |
| 18 | 2014 | 5 | |
| 19 | 2019 | 5 | |
| 20 | 2018 | 5 |
About Sheng-Ming Wang
Sheng-Ming Wang is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology, Human-Computer Interaction, Marketing and Health, Toxicology and Mutagenesis, having authored 54 papers that have together received 365 indexed citations. Recurring topics across this work include Atmospheric chemistry and aerosols (4 papers), Quality Function Deployment in Product Design (4 papers), Customer Service Quality and Loyalty (3 papers), Educational Games and Gamification (3 papers), Mitochondrial Function and Pathology (3 papers), Service and Product Innovation (3 papers), Augmented Reality Applications (3 papers) and Human Mobility and Location-Based Analysis (3 papers). The work is most often cited by research in Human-Computer Interaction (26 citations), Media Technology (20 citations), Cancer Research (33 citations), Biophysics (11 citations) and Computer Vision and Pattern Recognition (35 citations). Sheng-Ming Wang has collaborated with scholars based in China, Taiwan and Singapore. Frequent co-authors include Yayun Wang, Yanling Yang, Chun‐Qiu Dai, Jiaqi Wang, Tingting Luo, Fangfang Li, Zengzhao Chen, An‐Wu Xu, Zuojun Hu and Tuck−Yun Cheang. Their work appears in journals such as Atmospheric Environment, Sensors, Process Safety and Environmental Protection, Clinical & Translational Oncology and Future Internet.
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.