Ching‐Long Shih

1.7k citations
57 papers · 1.3k indexed · h-index 19

Impact in

Papers in

Ching‐Long Shih

53 papers receiving 1.2k citations

Peers

Ching‐Long Shih
Comparison fields: 5 of 70
  • Control and Systems Engineering 626
  • Biomedical Engineering 884
  • Computer Vision and Pattern Recognition 196
  • Genetics 99
  • Oral Surgery 56
Replace Amir Degani with:
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Alexander Winkler Germany
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Diansheng Chen China
Dennis Hong United States
Jung-Yup Kim South Korea
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Johannes Englsberger Germany
Ching‐Long Shih relative to Amir Degani Israel Amir Degani's profile →
Citations per field
00.5×9.9×
Amir Degani · 1×
Citations per year

Countries citing papers authored by Ching‐Long Shih

Since Specialization
Citations

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

Fields of papers citing papers by Ching‐Long Shih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20242
2 202017
3 20190
4 20152
5 20113
6 20111
7 2009210
8 200822
9 200668
10 200413
11 200466
12 20045
13 19990
14 19998
15 199817
16 19971
17 199633
18 199263
19 19915
20 19868

About Ching‐Long Shih

Ching‐Long Shih is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Automotive Engineering, Computer Graphics and Computer-Aided Design and Biomedical Engineering, having authored 57 papers that have together received 1.3k indexed citations. Recurring topics across this work include Robotic Locomotion and Control (21 papers), Control and Dynamics of Mobile Robots (17 papers), Prosthetics and Rehabilitation Robotics (12 papers), Robotics and Sensor-Based Localization (9 papers), Vehicle Dynamics and Control Systems (8 papers), Soil Mechanics and Vehicle Dynamics (7 papers), Robotic Path Planning Algorithms (7 papers) and Advanced Vision and Imaging (6 papers). The work is most often cited by research in Control and Systems Engineering (626 citations), Biomedical Engineering (884 citations), Computer Vision and Pattern Recognition (196 citations), Genetics (99 citations) and Oral Surgery (56 citations). Ching‐Long Shih has collaborated with scholars based in Taiwan, United States and France. Frequent co-authors include Christine Chevallereau, W.A. Gruver, Jessy W. Grizzle, Tsu‐Tian Lee, Chih‐Lyang Hwang, Hsiu‐Ming Wu, Won‐Young Lee, J.W. Grizzle, Charles A. Klein and Yong Zhu. Their work appears in journals such as Robotica, Robotics, The International Journal of Advanced Manufacturing Technology, Journal of Vibration and Control and Journal of Dynamic Systems Measurement and Control.

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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