Kun Yuan
- Gender Studies top 10%
- Diversity and Career in Medicine 2
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- Recommender Systems and Techniques 4
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- Advanced Graph Neural Networks 4
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- RNA modifications and cancer 4
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- School Choice and Performance 3
- Educational Assessment and Pedagogy 2
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- Ferroptosis and cancer prognosis 2
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- Esophageal Cancer Research and Treatment 2
Kun Yuan
28 papers receiving 288 citations
Peers
Comparison fields: 5 of 90
- Gender Studies 50
- Developmental and Educational Psychology 47
- Experimental and Cognitive Psychology 42
- Public Health, Environmental and Occupational Health 69
- Family Practice 5
Countries citing papers authored by Kun Yuan
This map shows the geographic impact of Kun Yuan'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 Kun Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Yuan more than expected).
Fields of papers citing papers by Kun Yuan
This network shows the impact of papers produced by Kun Yuan. 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 Kun Yuan. The network helps show where Kun Yuan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kun Yuan, 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 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 9 | |
| 5 | 2023 | 0 | |
| 6 | 2023 | 3 | |
| 7 | 2022 | 22 | |
| 8 | 2022 | 14 | |
| 9 | 2021 | 11 | |
| 10 | 2019 | 5 | |
| 11 | 2019 | 45 | |
| 12 | Diving into Optimization of Topology in Neural Networks | 2019 | 1 |
| 13 | 2018 | 17 | |
| 14 | Analysis on latex physiological parameters of Hevea brasiliensis plants at different tapping panel dryness extents. | 2016 | 4 |
| 15 | Measuring Deeper Learning Through Cognitively Demanding Test Items: Results from the Analysis of Six National and International Exams | 2014 | 4 |
| 16 | Molecular cloning and analysis of LEA14L2 gene from rubber tree (Hevea brasiliensis Muell. Arg.). | 2013 | 1 |
| 17 | 2013 | 33 | |
| 18 | A Big Apple for Educators: New York City's Experiment with Schoolwide Performance Bonuses. Final Evaluation Report. Monograph. | 2011 | 1 |
| 19 | 2011 | 4 | |
| 20 | Math Science Partnership of Southwest Pennsylvania: Measuring Progress toward Goals. Monograph. | 2009 | 0 |
About Kun Yuan
Kun Yuan is a scholar working on Forestry, Computer Graphics and Computer-Aided Design and General Agricultural and Biological Sciences, having authored 34 papers that have together received 310 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (4 papers), Advanced Graph Neural Networks (4 papers), RNA modifications and cancer (4 papers), School Choice and Performance (3 papers), Educational Assessment and Pedagogy (2 papers), Diversity and Career in Medicine (2 papers), Ferroptosis and cancer prognosis (2 papers) and Esophageal Cancer Research and Treatment (2 papers). The work is most often cited by research in Gender Studies (50 citations), Developmental and Educational Psychology (47 citations) and Experimental and Cognitive Psychology (42 citations). Kun Yuan has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Jeffrey T. Steedle, Alicia C. Alonzo, Marily Oppezzo, Richard Shavelson, Martha L. Elks, Kevin Busche, Xianguo Hu, Wenzhe Wang, Yufu Xu and R. Stephen Manuel.
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.