Shi Wang
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
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- Multimodal Machine Learning Applications
Papers in
-
- Topic Modeling 22
- Natural Language Processing Techniques 21
- Advanced Text Analysis Techniques 9
- Advanced Graph Neural Networks 4
- Co-authors
- Liaoyun Zhang (5 shared papers)Ailian Wang (5 shared papers)Yanjun Ma (1 shared paper)Wei He (1 shared paper)Yajuan Lyu (1 shared paper)Jing Liu (1 shared paper)Guohua Chen (1 shared paper)Yanan Cao (8 shared papers)
- Journals
- Neural Computing and Applications (5 papers)Applied Microbiology and Biotechnology (1 paper)Energy Technology (1 paper)Polymer Chemistry (1 paper)New Journal of Chemistry (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Shi Wang
80 papers receiving 746 citations
Peers
Comparison fields: 5 of 105
- Artificial Intelligence 282
- Computer Vision and Pattern Recognition 101
- Polymers and Plastics 65
- Electrical and Electronic Engineering 194
- Radiation 25
Countries citing papers authored by Shi Wang
This map shows the geographic impact of Shi 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 Shi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shi Wang more than expected).
Fields of papers citing papers by Shi Wang
This network shows the impact of papers produced by Shi 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 Shi Wang. The network helps show where Shi Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Shi 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 100 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 105 | |
| 2 | 2017 | 70 | |
| 3 | 2020 | 65 | |
| 4 | 2018 | 60 | |
| 5 | 2017 | 44 | |
| 6 | 2015 | 40 | |
| 7 | 2022 | 23 | |
| 8 | 2023 | 22 | |
| 9 | 2017 | 21 | |
| 10 | 2020 | 20 | |
| 11 | 2020 | 19 | |
| 12 | 2021 | 18 | |
| 13 | 2021 | 15 | |
| 14 | 2020 | 13 | |
| 15 | 2019 | 12 | |
| 16 | 2021 | 11 | |
| 17 | 2018 | 11 | |
| 18 | 2013 | 11 | |
| 19 | 2020 | 10 | |
| 20 | 2021 | 10 |
About Shi Wang
Shi Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Information Systems, having authored 100 papers that have together received 769 indexed citations. Recurring topics across this work include Topic Modeling (22 papers), Natural Language Processing Techniques (21 papers), Medical Imaging Techniques and Applications (10 papers), Advanced Text Analysis Techniques (9 papers), Radiation Detection and Scintillator Technologies (6 papers), Advanced X-ray and CT Imaging (5 papers), Advanced Graph Neural Networks (4 papers) and Advanced MRI Techniques and Applications (4 papers). The work is most often cited by research in Artificial Intelligence (282 citations), Computer Vision and Pattern Recognition (101 citations), Polymers and Plastics (65 citations), Electrical and Electronic Engineering (194 citations) and Radiation (25 citations). Shi Wang has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Liaoyun Zhang, Ailian Wang, Yanjun Ma, Wei He, Yajuan Lyu, Jing Liu, Guohua Chen, Yanan Cao, Fang Fang and Jie Chen. Their work appears in journals such as Neural Computing and Applications, Applied Microbiology and Biotechnology, Energy Technology, Polymer Chemistry and New Journal of Chemistry.
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.