Ching-Lung Chang

44 papers receiving 368 citations

Peers

Ching-Lung Chang
Comparison fields: 5 of 79
  • Modeling and Simulation 23
  • Computational Mechanics 96
  • Computer Networks and Communications 92
  • Control and Systems Engineering 75
  • Media Technology 21
Replace Pitikhate Sooraksa with:
Pitikhate Sooraksa Thailand
Shuai Lu China
M. R. Kaimal India
Dia Abualnadi Jordan
Narendra Kumar Dhar India
Noor M. Khan Pakistan
David Ricardo Cruz Mexico
Wang Yao-nan China
Enrique García Mexico
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Ching-Lung Chang relative to Pitikhate Sooraksa Thailand Pitikhate Sooraksa's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ching-Lung Chang

Since Specialization
Citations

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

Fields of papers citing papers by Ching-Lung Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ching-Lung Chang. 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-Lung Chang. The network helps show where Ching-Lung Chang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 198742
2 201930
3 202228
4 199023
5 202321
6 201021
7 202119
8 202215
9 202215
10 202212
11 202111
12 198811
13 200911
14 201610
15 20189
16 20229
17 20138
18 20148
19
Bounding the Sensing Data Collection Time with Ring-based Routing for Industrial Wireless Sensor Networks
20207
20 20207

About Ching-Lung Chang

Ching-Lung Chang is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing, having authored 47 papers that have together received 394 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (4 papers), Control Systems and Identification (4 papers), Energy Efficient Wireless Sensor Networks (4 papers), Image and Video Quality Assessment (4 papers), Peer-to-Peer Network Technologies (4 papers), Multimedia Communication and Technology (3 papers), Advanced Adaptive Filtering Techniques (3 papers) and Advanced Numerical Methods in Computational Mathematics (3 papers). The work is most often cited by research in Modeling and Simulation (23 citations), Computational Mechanics (96 citations), Computer Networks and Communications (92 citations), Control and Systems Engineering (75 citations) and Media Technology (21 citations). Ching-Lung Chang has collaborated with scholars based in Taiwan, Pakistan and China. Frequent co-authors include Max Gunzburger, Muhammad Asif Zahoor Raja, Naveed Ishtiaq Chaudhary, Chi‐Min Shu, Shuo-Tsung Chen, Yue‐Shan Chang, Muhammad Faizan Malik, Chuan‐Yu Chang, Khalid Mehmood Cheema and Chao‐Tung Yang. Their work appears in journals such as Sensors, Applied Mathematics and Computation, Journal of the Taiwan Institute of Chemical Engineers, Computer Networks and International Journal of Distance Education Technologies.

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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