Ling‐Ling Tsai

1.3k citations
30 papers · 961 · h-index 15

Impact in

Papers in

Ling‐Ling Tsai

30 papers receiving 922 citations

Peers

Ling‐Ling Tsai
Comparison fields: 5 of 94
  • Experimental and Cognitive Psychology 401
  • Endocrine and Autonomic Systems 140
  • Cognitive Neuroscience 301
  • Aging 15
  • Applied Psychology 26
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Timothy H. Monk United States
Päivi Polo-Kantola Finland
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Shingo Kitamura Japan
Jung Hie Lee South Korea
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Yoshiro Sugita Japan
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Shuichiro Shirakawa Japan
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Citations per field
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Citations per year

Countries citing papers authored by Ling‐Ling Tsai

Since Specialization
Citations

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

Fields of papers citing papers by Ling‐Ling Tsai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ling‐Ling Tsai. 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 Ling‐Ling Tsai. The network helps show where Ling‐Ling Tsai may publish in the future.

Co-authors

The 25 scholars most cited alongside Ling‐Ling Tsai, 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 Ling‐Ling Tsai Line = papers co-authored together Ling‐Ling Tsai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004246
2 2016175
3 200579
4 200569
5 201647
6 200744
7 199332
8 200232
9 201031
10 200430
11
Selection of valid and reliable EEG features for predicting auditory and visual alertness levels.
200122
12 200921
13 199418
14 199215
15 200914
16 201613
17 200412
18 201510
19 19958
20 20088

About Ling‐Ling Tsai

Ling‐Ling Tsai is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Endocrine and Autonomic Systems, Physiology and Cellular and Molecular Neuroscience, having authored 30 papers that have together received 961 indexed citations. Recurring topics across this work include Sleep and Wakefulness Research (9 papers), Sleep and Work-Related Fatigue (8 papers), Circadian rhythm and melatonin (7 papers), Sleep and related disorders (5 papers), Adipose Tissue and Metabolism (4 papers), Chronic Obstructive Pulmonary Disease (COPD) Research (4 papers), Photoreceptor and optogenetics research (3 papers) and Neural and Behavioral Psychology Studies (2 papers). The work is most often cited by research in Experimental and Cognitive Psychology (401 citations), Endocrine and Autonomic Systems (140 citations), Cognitive Neuroscience (301 citations), Aging (15 citations) and Applied Psychology (26 citations). Ling‐Ling Tsai has collaborated with scholars based in Taiwan, Australia and United States. Frequent co-authors include Shengping Li, Shulan Hsieh, Jennifer Alison, Zoe McKeough, David K. McKenzie, Renae J. McNamara, Bernard M. Bergmann, Chung J. Kuo, Ruey‐Song Huang and Yu‐Che Tsai. Their work appears in journals such as SLEEP, Brain Research, Chronic Respiratory Disease, Journal of Sleep Research and Neuroscience.

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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