Kai‐Yuan Shih

14 total papers · 1.1k total citations
12 papers, 948 citations indexed

About

Kai‐Yuan Shih is a scholar working on Radiology, Nuclear Medicine and Imaging, Electrical and Electronic Engineering and Materials Chemistry. According to data from OpenAlex, Kai‐Yuan Shih has authored 12 papers receiving a total of 948 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Electrical and Electronic Engineering and 4 papers in Materials Chemistry. Recurrent topics in Kai‐Yuan Shih's work include Plasma Applications and Diagnostics (12 papers), Electrohydrodynamics and Fluid Dynamics (10 papers) and Plasma Diagnostics and Applications (6 papers). Kai‐Yuan Shih is often cited by papers focused on Plasma Applications and Diagnostics (12 papers), Electrohydrodynamics and Fluid Dynamics (10 papers) and Plasma Diagnostics and Applications (6 papers). Kai‐Yuan Shih collaborates with scholars based in United States, Romania and Japan. Kai‐Yuan Shih's co-authors include Bruce R. Locke, Radu Burlică, David L. Balkwill, R. Gary Grim, Bogdan Hnatiuc and W.C. Finney and has published in prestigious journals such as Industrial & Engineering Chemistry Research, IEEE Transactions on Industry Applications and Plasma Sources Science and Technology.

In The Last Decade

Kai‐Yuan Shih

11 papers receiving 923 citations

Hit Papers

Review of the methods to ... 2011 2026 2016 2021 2011 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kai‐Yuan Shih 831 668 217 92 70 12 948
Wflm Wilfred Hoeben 670 0.8× 538 0.8× 270 1.2× 179 1.9× 36 0.5× 36 921
Eva Doležalová 1.1k 1.3× 723 1.1× 120 0.6× 69 0.8× 155 2.2× 7 1.2k
Avaly Doubla 668 0.8× 463 0.7× 159 0.7× 131 1.4× 63 0.9× 20 857
Vesna V. Kovačević 767 0.9× 687 1.0× 99 0.5× 80 0.9× 71 1.0× 24 926
Matthew J. Pavlovich 830 1.0× 617 0.9× 107 0.5× 23 0.3× 119 1.7× 10 1.1k
Arne Vandenbroucke 775 0.9× 552 0.8× 810 3.7× 39 0.4× 61 0.9× 25 1.2k
Georges Kamgang‐Youbi 792 1.0× 553 0.8× 142 0.7× 109 1.2× 88 1.3× 28 1.0k
Chen Chen 736 0.9× 486 0.7× 87 0.4× 50 0.5× 101 1.4× 24 929
Barbora Tarabová 812 1.0× 610 0.9× 85 0.4× 20 0.2× 120 1.7× 13 917
Baghdad Benstaali 452 0.5× 334 0.5× 232 1.1× 371 4.0× 40 0.6× 12 957

Countries citing papers authored by Kai‐Yuan Shih

Since Specialization
Citations

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

Fields of papers citing papers by Kai‐Yuan Shih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kai‐Yuan Shih. 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 Kai‐Yuan Shih. The network helps show where Kai‐Yuan Shih may publish in the future.

Co-authorship network of co-authors of Kai‐Yuan Shih

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

All Works

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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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