Runqi Wang
Impact in
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- Advanced Neural Network Applications
Papers in
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- Advanced Neural Network Applications 5
- Multimodal Machine Learning Applications 3
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- Domain Adaptation and Few-Shot Learning 5
- Adversarial Robustness in Machine Learning 3
- Co-authors
- Baochang Zhang (10 shared papers)John Kemeny (2 shared papers)Han‐Wei Shen (1 shared paper)Jingyi Shen (1 shared paper)Lei Deng (2 shared papers)Shuo Zhang (1 shared paper)David Doermann (3 shared papers)Guodong Guo (2 shared papers)
- Journals
- International Journal of Computer Vision (2 papers)Sustainability (1 paper)Journal of the American Chemical Society (1 paper)Thermal Science and Engineering Progress (1 paper)Journal of the Energy Institute (1 paper)
- Partner nations
- ChinaUnited StatesSweden
In The Last Decade
Runqi Wang
26 papers receiving 200 citations
Peers
Comparison fields: 5 of 95
- Music 6
- Computer Vision and Pattern Recognition 35
- Cancer Research 26
- Neurology 12
- Fuel Technology 1
Countries citing papers authored by Runqi Wang
This map shows the geographic impact of Runqi 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 Runqi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Runqi Wang more than expected).
Fields of papers citing papers by Runqi Wang
This network shows the impact of papers produced by Runqi 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 Runqi Wang. The network helps show where Runqi Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Runqi 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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 21 | |
| 2 | 2021 | 18 | |
| 3 | 2016 | 17 | |
| 4 | 2020 | 15 | |
| 5 | 2021 | 14 | |
| 6 | 2022 | 13 | |
| 7 | 2021 | 13 | |
| 8 | A Study of the Coupling Between Mechanical Loading and Flow Properties in Tuffaceous Rock | 1994 | 10 |
| 9 | 2023 | 10 | |
| 10 | 2020 | 9 | |
| 11 | 2023 | 9 | |
| 12 | 2021 | 8 | |
| 13 | 2025 | 7 | |
| 14 | 2018 | 6 | |
| 15 | 2023 | 6 | |
| 16 | 2022 | 6 | |
| 17 | 2020 | 5 | |
| 18 | 2022 | 4 | |
| 19 | 2025 | 3 | |
| 20 | 2024 | 3 |
About Runqi Wang
Runqi Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Molecular Biology and Mechanics of Materials, having authored 32 papers that have together received 206 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Domain Adaptation and Few-Shot Learning (5 papers), CCD and CMOS Imaging Sensors (4 papers), COVID-19 diagnosis using AI (3 papers), Adversarial Robustness in Machine Learning (3 papers), Landslides and related hazards (3 papers), Rock Mechanics and Modeling (3 papers) and Multimodal Machine Learning Applications (3 papers). The work is most often cited by research in Music (6 citations), Computer Vision and Pattern Recognition (35 citations), Cancer Research (26 citations), Neurology (12 citations) and Fuel Technology (1 citation). Runqi Wang has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Baochang Zhang, John Kemeny, Han‐Wei Shen, Jingyi Shen, Lei Deng, Shuo Zhang, David Doermann, Guodong Guo, Yiping Wang and Yun Wang. Their work appears in journals such as International Journal of Computer Vision, Sustainability, Journal of the American Chemical Society, Thermal Science and Engineering Progress and Journal of the Energy Institute.
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.