Chia‐Ying Lee

2.5k total citations · 1 hit paper
50 papers, 1.8k citations indexed

About

Chia‐Ying Lee is a scholar working on Cognitive Neuroscience, Atmospheric Science and Developmental and Educational Psychology. According to data from OpenAlex, Chia‐Ying Lee has authored 50 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Cognitive Neuroscience, 22 papers in Atmospheric Science and 18 papers in Developmental and Educational Psychology. Recurrent topics in Chia‐Ying Lee's work include Tropical and Extratropical Cyclones Research (19 papers), Reading and Literacy Development (18 papers) and Neurobiology of Language and Bilingualism (18 papers). Chia‐Ying Lee is often cited by papers focused on Tropical and Extratropical Cyclones Research (19 papers), Reading and Literacy Development (18 papers) and Neurobiology of Language and Bilingualism (18 papers). Chia‐Ying Lee collaborates with scholars based in Taiwan, United States and United Kingdom. Chia‐Ying Lee's co-authors include Suzana J. Camargo, Adam H. Sobel, Michael K. Tippett, Chun-Hsien Hsu, Shuyi S. Chen, Jie-Li Tsai, Ovid J. L. Tzeng, Daisy L. Hung, Allison A. Wing and Tim Hall and has published in prestigious journals such as Science, Nature Communications and NeuroImage.

In The Last Decade

Chia‐Ying Lee

46 papers receiving 1.7k citations

Hit Papers

Human influence on tropical cyclone intensity 2016 2026 2019 2022 2016 100 200 300

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chia‐Ying Lee Taiwan 23 808 634 593 494 433 50 1.8k
Yu-Lin Chang Taiwan 24 339 0.4× 396 0.6× 58 0.1× 90 0.2× 578 1.3× 61 1.2k
Andrew W. Ellis United States 23 474 0.6× 606 1.0× 631 1.1× 621 1.3× 20 0.0× 51 1.8k
Thomas F. Gross United States 23 291 0.4× 228 0.4× 239 0.4× 86 0.2× 709 1.6× 61 1.5k
Thomas J. Moore United States 21 141 0.2× 210 0.3× 291 0.5× 64 0.1× 203 0.5× 49 1.2k
Yunfei Zhang China 10 181 0.2× 433 0.7× 139 0.2× 394 0.8× 24 0.1× 23 1.1k
Michael Clark United States 22 321 0.4× 153 0.2× 633 1.1× 286 0.6× 12 0.0× 69 3.3k
W.S. Brown United States 28 111 0.1× 327 0.5× 171 0.3× 45 0.1× 54 0.1× 86 2.2k
Andrew Shaw United Kingdom 22 496 0.6× 426 0.7× 189 0.3× 11 0.0× 840 1.9× 43 1.5k
Mark Zimmermann United States 20 154 0.2× 602 0.9× 290 0.5× 12 0.0× 286 0.7× 59 1.3k
David Kastak United States 18 225 0.3× 139 0.2× 178 0.3× 377 0.8× 1.2k 2.9× 39 2.2k

Countries citing papers authored by Chia‐Ying Lee

Since Specialization
Citations

This map shows the geographic impact of Chia‐Ying Lee'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 Chia‐Ying Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chia‐Ying Lee more than expected).

Fields of papers citing papers by Chia‐Ying Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia‐Ying Lee. 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 Chia‐Ying Lee. The network helps show where Chia‐Ying Lee may publish in the future.

Co-authorship network of co-authors of Chia‐Ying Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Chia‐Ying Lee. A scholar is included among the top collaborators of Chia‐Ying Lee 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 Chia‐Ying Lee. Chia‐Ying Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Lee, Chia‐Ying, et al.. (2025). Climate Change Impact on the ENSO–TC Relationship in CMIP6: Synthetic TC Analysis. Journal of Climate. 38(20). 5595–5614.
2.
Camargo, Suzana J., Chia‐Ying Lee, Jonathan Lin, et al.. (2025). Improving analogues-based detection & attribution approaches for hurricanes. Environmental Research Letters. 20(2). 24042–24042. 1 indexed citations
3.
Patricola, Christina M., et al.. (2025). Multidecadal Fluctuations in the Observed ENSO‐Tropical Cyclone Teleconnection. Geophysical Research Letters. 52(22).
5.
Emanuel, Kerry, Tommaso Alberti, Suzana J. Camargo, et al.. (2025). CYCLOPs: a Unified Framework for Surface Flux-Driven Cyclones Outside the Tropics. Weather and Climate Dynamics. 6(3). 901–926. 1 indexed citations
6.
Lee, Chia‐Ying, Adam H. Sobel, Michael K. Tippett, et al.. (2023). Climate Change Signal in Atlantic Tropical Cyclones Today and Near Future. Earth s Future. 11(11). 3 indexed citations
7.
Cheng, Shih-kuen, et al.. (2021). The neural basis of compound word processing revealed by varying semantic transparency and morphemic neighborhood size. Brain and Language. 221. 104985–104985. 2 indexed citations
8.
Wang, Shuguang, Adam H. Sobel, Chia‐Ying Lee, et al.. (2020). Propagating Mechanisms of the 2016 Summer BSISO Event: Air‐Sea Coupling, Vorticity, and Moisture. Journal of Geophysical Research Atmospheres. 126(2). 10 indexed citations
9.
Lee, Chia‐Ying, Michael K. Tippett, Adam H. Sobel, & Suzana J. Camargo. (2018). An Environmentally Forced Tropical Cyclone Hazard Model. Journal of Advances in Modeling Earth Systems. 10(1). 223–241. 116 indexed citations
10.
Hsu, Chun-Hsien, et al.. (2017). The Acquisition of Orthographic Knowledge: Evidence from the Lexicality Effects on N400. Frontiers in Psychology. 8. 433–433. 14 indexed citations
11.
Hsu, Chun-Hsien, Chia‐Ying Lee, & Wei‐Kuang Liang. (2016). An improved method for measuring mismatch negativity using ensemble empirical mode decomposition. Journal of Neuroscience Methods. 264. 78–85. 28 indexed citations
12.
Chang, Ya‐Ning, Chun-Hsien Hsu, Jie-Li Tsai, Chien‐Liang Chen, & Chia‐Ying Lee. (2015). A psycholinguistic database for traditional Chinese character naming. Behavior Research Methods. 48(1). 112–122. 45 indexed citations
13.
Tong, Xiuhong, Catherine McBride, Juan Zhang, et al.. (2014). Neural correlates of acoustic cues of English lexical stress in Cantonese-speaking children. Brain and Language. 138. 61–70. 15 indexed citations
14.
Hsu, Chun-Hsien, et al.. (2014). The neural generators of the mismatch responses to Mandarin lexical tones: An MEG study. Brain Research. 1582. 154–166. 21 indexed citations
15.
Lee, Chia‐Ying, et al.. (2013). The impact of spectral resolution on the mismatch response to Mandarin Chinese tones: An ERP study of cochlear implant simulations. Clinical Neurophysiology. 125(8). 1568–1575. 17 indexed citations
16.
Hsu, Chun-Hsien, Chia‐Ying Lee, & Alec Marantz. (2010). Effects of visual complexity and sublexical information in the occipitotemporal cortex in the reading of Chinese phonograms: A single-trial analysis with MEG. Brain and Language. 117(1). 1–11. 29 indexed citations
17.
Lee, Chia‐Ying, et al.. (2007). Temporal dynamics of the consistency effect in reading Chinese: an event-related potentials study. Neuroreport. 18(2). 147–151. 65 indexed citations
18.
Huang, Feng‐Ying, Chia‐Ying Lee, Jie-Li Tsai, et al.. (2006). Orthographic neighborhood effects in reading Chinese two-character words. Neuroreport. 17(10). 1061–1065. 43 indexed citations
19.
Ahrens, Kathleen, et al.. (2005). Functional MRI of conventional and anomalous metaphors in Mandarin Chinese. Brain and Language. 100(2). 163–171. 114 indexed citations
20.
Lee, Chia‐Ying, Jie-Li Tsai, Wen‐Jui Kuo, et al.. (2004). Neuronal correlates of consistency and frequency effects on Chinese character naming: an event-related fMRI study. NeuroImage. 23(4). 1235–1245. 85 indexed citations

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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