Chaoran Wang

102 papers receiving 1.5k citations

Chaoran Wang's Hit Papers

Investigating L2 writers' critical AI literacy in AI-assisted writing: An APSE model 2025 · 32 citations
320+1Years since publication204060

Peers

Chaoran Wang
Comparison fields: 5 of 151
  • Health Informatics 59
  • Analytical Chemistry 166
  • Computer Science Applications 81
  • Pharmacology 122
  • Developmental Neuroscience 53
Replace Rashmi K. Ambasta with:
Rashmi K. Ambasta India
Rohan Gupta India
Fawaz Alasmari Saudi Arabia
Santosh Kumar Bharti India
Qingxia Yang China
Jianxin Chen China
Jiansong Fang China
Rui An China
Chaoran Wang relative to Rashmi K. Ambasta India Rashmi K. Ambasta's profile →
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Rashmi K. Ambasta · 1×
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Countries citing papers authored by Chaoran Wang

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authors

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.

Border = papers with Chaoran Wang Line = papers co-authored together Chaoran Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 108 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020120
2 201483
3 201980
4 201062
5
Exploring Students’ Generative AI-Assisted Writing Processes: Perceptions and Experiences from Native and Nonnative English Speakers
Hit paper breakdown →
202460
6 201851
7 202439
8 202439
9 201338
10 201937
11 201937
12 202136
13 201935
14 202333
15
Investigating L2 writers' critical AI literacy in AI-assisted writing: An APSE model
Hit paper breakdown →
202532
16 202132
17 201630
18 201830
19 201227
20 201226

About Chaoran Wang

Chaoran Wang is a scholar working on Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering, Molecular Biology, Spectroscopy and Pharmacology, having authored 108 papers that have together received 1.5k 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 (5 papers) and Artificial Intelligence in Healthcare and Education (5 papers). The work is most often cited by research in Health Informatics (59 citations), Analytical Chemistry (166 citations), Computer Science Applications (81 citations), Pharmacology (122 citations) and Developmental Neuroscience (53 citations). Chaoran Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Zhimou Guo, Xinmiao Liang, Honggang Fan, Yuan Zhao, Xiuli Zhang, Xiujing Feng, Curtis J. Bonk, Xingliang Li, Shumin Zhang and Tianyuan Yang. Their work appears in journals such as Optics & Laser Technology, Journal of Separation Science, Journal of Chromatography A, Optics Express and Journal of Chromatography B.

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.

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