Chin‐Chin Wu
Impact in
- Modeling and Simulation top 2%
- Fractional Differential Equations Solutions
- Applied Mathematics top 5%
Papers in
-
- Mathematical Biology Tumor Growth 5
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- Autism Spectrum Disorder Research 16
- Co-authors
- Jong‐Shenq GuoXinfu ChenYuh‐Ming HouChung‐Hsin ChiangChing-Lin ChuKen-Ichi NakamuraHiroshi MatanoFrançois Hamel
- Journals
- Journal of Autism and Developmental Disorders (5 papers)Journal of Differential Equations (4 papers)Applied Mathematics Letters (4 papers)Autism (3 papers)Discrete and Continuous Dynamical Systems - B (3 papers)
- Partner nations
- TaiwanUnited KingdomJapan
In The Last Decade
Chin‐Chin Wu
42 papers receiving 464 citations
Peers
Comparison fields: 5 of 47
- Modeling and Simulation 129
- Applied Mathematics 90
- Public Health, Environmental and Occupational Health 251
- Cognitive Neuroscience 144
- Mathematical Physics 66
Countries citing papers authored by Chin‐Chin Wu
This map shows the geographic impact of Chin‐Chin Wu'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 Chin‐Chin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chin‐Chin Wu more than expected).
Fields of papers citing papers by Chin‐Chin Wu
This network shows the impact of papers produced by Chin‐Chin Wu. 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 Chin‐Chin Wu. The network helps show where Chin‐Chin Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Chin‐Chin Wu, 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 | 2024 | 0 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 5 | |
| 4 | 2023 | 1 | |
| 5 | 2022 | 15 | |
| 6 | 2022 | 5 | |
| 7 | 2020 | 4 | |
| 8 | 2020 | 31 | |
| 9 | 2020 | 9 | |
| 10 | 2018 | 29 | |
| 11 | 2018 | 6 | |
| 12 | Traveling wave solutions for a discrete diffusive epidemic model | 2016 | 27 |
| 13 | 2016 | 51 | |
| 14 | 2015 | 20 | |
| 15 | 2012 | 3 | |
| 16 | 2012 | 17 | |
| 17 | 2012 | 2 | |
| 18 | 2009 | 2 | |
| 19 | 2009 | 27 | |
| 20 | 2004 | 5 |
About Chin‐Chin Wu
Chin‐Chin Wu is a scholar working on Modeling and Simulation, Cognitive Neuroscience, Mathematical Physics, Applied Mathematics and Public Health, Environmental and Occupational Health, having authored 44 papers that have together received 495 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (18 papers), Autism Spectrum Disorder Research (16 papers), Family and Disability Support Research (12 papers), Evolution and Genetic Dynamics (8 papers), Nonlinear Dynamics and Pattern Formation (8 papers), Advanced Mathematical Modeling in Engineering (6 papers), Stability and Controllability of Differential Equations (6 papers) and Mathematical Biology Tumor Growth (5 papers). The work is most often cited by research in Modeling and Simulation (129 citations), Applied Mathematics (90 citations), Public Health, Environmental and Occupational Health (251 citations), Cognitive Neuroscience (144 citations) and Mathematical Physics (66 citations). Chin‐Chin Wu has collaborated with scholars based in Taiwan, United Kingdom and Japan. Frequent co-authors include Jong‐Shenq Guo, Xinfu Chen, Yuh‐Ming Hou, Chung‐Hsin Chiang, Ching-Lin Chu, Ken-Ichi Nakamura, Hiroshi Matano, François Hamel, Wei‐Tsuen Soong and Zhengce Zhang. Their work appears in journals such as Journal of Autism and Developmental Disorders, Journal of Differential Equations, Applied Mathematics Letters, Autism and Discrete and Continuous Dynamical Systems - 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.