Feng‐Ying Huang
- Molecular Biology
- Cognitive Neuroscience top 5%
- Immunology
- Developmental and Educational Psychology top 5%
- Experimental and Cognitive Psychology top 5%
- Co-authors
- Guang‐Hong TanYingying LinKara D. FedermeierChia‐Lin LeeOvid J. L. TzengChih‐Mao HuangYonghao HuangZhuoxuan Lu
- Topics
- Neurobiology of Language and Bilingualism (15 papers)Reading and Literacy Development (9 papers)Nanoplatforms for cancer theranostics (7 papers)
- Cited by
- Cognitive NeuroscienceDevelopmental and Educational PsychologyExperimental and Cognitive Psychology
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEBiomaterials
- Partner nations
- ChinaTaiwanUnited States
In The Last Decade
Feng‐Ying Huang
91 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 144
- Molecular Biology 395
- Cognitive Neuroscience 373
- Immunology 201
- Developmental and Educational Psychology 195
- Experimental and Cognitive Psychology 188
Countries citing papers authored by Feng‐Ying Huang
This map shows the geographic impact of Feng‐Ying Huang'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 Feng‐Ying Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feng‐Ying Huang more than expected).
Fields of papers citing papers by Feng‐Ying Huang
This network shows the impact of papers produced by Feng‐Ying Huang. 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 Feng‐Ying Huang. The network helps show where Feng‐Ying Huang may publish in the future.
Co-authorship network of co-authors of Feng‐Ying Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Feng‐Ying Huang. A scholar is included among the top collaborators of Feng‐Ying Huang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Feng‐Ying Huang. Feng‐Ying Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 20 | |
| 5 | 2 | |
| 6 | 10 | |
| 7 | 11 | |
| 8 | 17 | |
| 9 | The New Science of Learning: Using the Power and Potential of the Brain to Inform Digital Learning | 5 |
| 10 | 21 | |
| 11 | 2 | |
| 12 | 13 | |
| 13 | 11 | |
| 14 | 24 | |
| 15 | 3 | |
| 16 | 12 | |
| 17 | The sublexical semantic ambiguity effects for reading Chinese disyllabic compounds | 1 |
| 18 | 5 | |
| 19 | 43 | |
| 20 | 40 |
About Feng‐Ying Huang
Feng‐Ying Huang is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Developmental and Educational Psychology, having authored 95 papers that have together received 1.5k indexed citations. Recurring topics across this work include Neurobiology of Language and Bilingualism (15 papers), Reading and Literacy Development (9 papers) and Nanoplatforms for cancer theranostics (7 papers). The work is most often cited by research in Cognitive Neuroscience (373 citations), Developmental and Educational Psychology (195 citations) and Experimental and Cognitive Psychology (188 citations). Feng‐Ying Huang has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Guang‐Hong Tan, Yingying Lin, Kara D. Federmeier, Chia‐Lin Lee, Ovid J. L. Tzeng, Chih‐Mao Huang, Yonghao Huang, Zhuoxuan Lu, Jie-Li Tsai and Chia‐Ying Lee. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Biomaterials.
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.