Shaokun Wang
Impact in
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- Distributed Control Multi-Agent Systems
- Neural Networks Stability and Synchronization
Papers in
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- Advanced Chemical Physics Studies 21
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- Domain Adaptation and Few-Shot Learning 4
- Co-authors
- Dongmei Xie (1 shared paper)Yueshu Gu (21 shared papers)Qingzhu Zhang (21 shared papers)Yi-der Chen (1 shared paper)Arthur Sherman (1 shared paper)Xiangwei Meng (1 shared paper)Li Pang (2 shared papers)Yongliang Xu (4 shared papers)
In The Last Decade
Shaokun Wang
62 papers receiving 606 citations
Peers
Comparison fields: 5 of 124
- Catalysis 34
- Computer Networks and Communications 88
- Cancer Research 44
- Atomic and Molecular Physics, and Optics 83
- Artificial Intelligence 77
Countries citing papers authored by Shaokun Wang
This map shows the geographic impact of Shaokun 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 Shaokun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaokun Wang more than expected).
Fields of papers citing papers by Shaokun Wang
This network shows the impact of papers produced by Shaokun 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 Shaokun Wang. The network helps show where Shaokun Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Shaokun 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 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 79 | |
| 2 | 2021 | 46 | |
| 3 | 2008 | 43 | |
| 4 | 2022 | 32 | |
| 5 | 2023 | 28 | |
| 6 | 2016 | 24 | |
| 7 | 2021 | 22 | |
| 8 | 2021 | 19 | |
| 9 | 2002 | 19 | |
| 10 | 2013 | 19 | |
| 11 | 2021 | 18 | |
| 12 | 2019 | 16 | |
| 13 | 2024 | 14 | |
| 14 | 2001 | 14 | |
| 15 | 2021 | 14 | |
| 16 | 2022 | 13 | |
| 17 | 2001 | 13 | |
| 18 | 2022 | 12 | |
| 19 | 2022 | 11 | |
| 20 | 2016 | 11 |
About Shaokun Wang
Shaokun Wang is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence, Atmospheric Science, Catalysis and Electrical and Electronic Engineering, having authored 66 papers that have together received 618 indexed citations. Recurring topics across this work include Advanced Chemical Physics Studies (21 papers), Atmospheric chemistry and aerosols (8 papers), Atmospheric Ozone and Climate (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Ammonia Synthesis and Nitrogen Reduction (4 papers), Catalytic Processes in Materials Science (4 papers), Molecular Junctions and Nanostructures (4 papers) and Catalysis and Oxidation Reactions (4 papers). The work is most often cited by research in Catalysis (34 citations), Computer Networks and Communications (88 citations), Cancer Research (44 citations), Atomic and Molecular Physics, and Optics (83 citations) and Artificial Intelligence (77 citations). Shaokun Wang has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Dongmei Xie, Yueshu Gu, Qingzhu Zhang, Yi-der Chen, Arthur Sherman, Xiangwei Meng, Li Pang, Yongliang Xu, Lanyun Wang and Liqiang Nie. Their work appears in journals such as The Journal of Physical Chemistry A, Chemical Physics Letters, The Journal of Chemical Physics, Chinese Journal of Chemistry and Advanced Materials Technologies.
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.