Yejing Wang
Impact in
- Biomaterials top 2%
- Silk-based biomaterials and applications
- Electrospun Nanofibers in Biomedical Applications
- Rehabilitation top 2%
- Wound Healing and Treatments
Papers in
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- Coding theory and cryptography 6
- Topic Modeling 6
- Advanced Graph Neural Networks 6
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- Recommender Systems and Techniques 17
- Co-authors
- Huawei He (18 shared papers)Ping Zhao (11 shared papers)Reihaneh Safavi–Naini (12 shared papers)Hua Zuo (8 shared papers)Rui Cai (7 shared papers)Qingyou Xia (10 shared papers)Gang Tao (8 shared papers)Gang Tao (4 shared papers)
In The Last Decade
Yejing Wang
60 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 117
- Biomaterials 581
- Rehabilitation 216
- Microbiology 90
- Molecular Medicine 65
- Information Systems 204
Countries citing papers authored by Yejing Wang
This map shows the geographic impact of Yejing 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 Yejing Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yejing Wang more than expected).
Fields of papers citing papers by Yejing Wang
This network shows the impact of papers produced by Yejing 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 Yejing Wang. The network helps show where Yejing Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yejing 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 | 2019 | 204 | |
| 2 | 2017 | 152 | |
| 3 | 2019 | 146 | |
| 4 | 2017 | 115 | |
| 5 | 2000 | 57 | |
| 6 | 2003 | 54 | |
| 7 | 2018 | 49 | |
| 8 | 2007 | 49 | |
| 9 | 2022 | 45 | |
| 10 | 2019 | 40 | |
| 11 | 2022 | 37 | |
| 12 | 2023 | 31 | |
| 13 | 2007 | 31 | |
| 14 | 2017 | 30 | |
| 15 | 2003 | 28 | |
| 16 | 2023 | 25 | |
| 17 | 2007 | 25 | |
| 18 | 2023 | 24 | |
| 19 | 2004 | 16 | |
| 20 | 2016 | 15 |
About Yejing Wang
Yejing Wang is a scholar working on Artificial Intelligence, Information Systems, Biomaterials, Molecular Biology and Electrical and Electronic Engineering, having authored 66 papers that have together received 1.4k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (17 papers), Silk-based biomaterials and applications (14 papers), Advanced Steganography and Watermarking Techniques (7 papers), Coding theory and cryptography (6 papers), Topic Modeling (6 papers), Advanced Graph Neural Networks (6 papers), Neurobiology and Insect Physiology Research (5 papers) and Advanced Wireless Communication Techniques (5 papers). The work is most often cited by research in Biomaterials (581 citations), Rehabilitation (216 citations), Microbiology (90 citations), Molecular Medicine (65 citations) and Information Systems (204 citations). Yejing Wang has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Huawei He, Ping Zhao, Reihaneh Safavi–Naini, Hua Zuo, Rui Cai, Qingyou Xia, Gang Tao, Gang Tao, Xiangyu Zhao and Pengchao Guo. Their work appears in journals such as Molecules, International Journal of Biological Macromolecules, Materials Science and Engineering C, Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics and Applied Biochemistry and Biotechnology.
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.