Chaoran Wang
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education 5
- Analytical Chemistry top 2%
- Chromatography in Natural Products 8
- Pharmacology top 5%
- Pharmacological Effects of Natural Compounds 6
- Developmental Neuroscience top 10%
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- Online Learning and Analytics 7
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- Advanced Fiber Laser Technologies 21
- Laser-Matter Interactions and Applications 11
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- Photonic Crystal and Fiber Optics 16
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- Analytical Chemistry and Chromatography 14
Chaoran Wang
94 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Health Informatics 53
- Analytical Chemistry 168
- Pharmacology 144
- Developmental Neuroscience 67
- Computer Science Applications 78
Countries citing papers authored by Chaoran Wang
This map shows the geographic impact of Chaoran 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 Chaoran Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chaoran Wang more than expected).
Fields of papers citing papers by Chaoran Wang
This network shows the impact of papers produced by Chaoran 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 Chaoran Wang. The network helps show where Chaoran Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Chaoran 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | Investigating L2 writers' critical AI literacy in AI-assisted writing: An APSE modelbreakdown → | 2025 | 20 |
| 4 | 2025 | 0 | |
| 5 | 2025 | 3 | |
| 6 | 2025 | 2 | |
| 7 | 2025 | 0 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 3 | |
| 10 | 2024 | 7 | |
| 11 | 2024 | 2 | |
| 12 | 2024 | 4 | |
| 13 | 2023 | 8 | |
| 14 | 2023 | 1 | |
| 15 | 2023 | 7 | |
| 16 | 2021 | 31 | |
| 17 | Fast-forwarding to desired visualizations with zenvisage | 2017 | 15 |
| 18 | Why Are My Chinese Students so Quiet?: A Classroom Ethnographic Study of Chinese Students’ Peer Review Activities in an American Multilingual Writing Class | 2016 | 3 |
| 19 | Catechin:Biological Activity and Application Potential | 2011 | 0 |
| 20 | 2010 | 25 |
About Chaoran Wang
Chaoran Wang is a scholar working on Health Informatics, Computer Science Applications, Pharmacology, Acoustics and Ultrasonics and Theoretical Computer Science, having authored 107 papers that have together received 1.4k indexed citations. Recurring topics across this work include Advanced Fiber Laser Technologies (21 papers), Photonic Crystal and Fiber Optics (16 papers), Analytical Chemistry and Chromatography (14 papers), Laser-Matter Interactions and Applications (11 papers), Chromatography in Natural Products (8 papers), Online Learning and Analytics (7 papers), Pharmacological Effects of Natural Compounds (6 papers) and Artificial Intelligence in Healthcare and Education (5 papers). The work is most often cited by research in Health Informatics (53 citations), Analytical Chemistry (168 citations), Pharmacology (144 citations), Developmental Neuroscience (67 citations) and Computer Science Applications (78 citations). Chaoran Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Zhimou Guo, Xinmiao Liang, Yuan Zhao, Honggang Fan, Xiuli Zhang, Xiujing Feng, Manyu Song, Tianyuan Yang, Curtis J. Bonk and Shumin Zhang. Their work appears in journals such as Journal of Separation Science, Optics & Laser Technology, Journal of Chromatography A, Optics Express and Journal of Lightwave Technology.
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.