Shu-Han Juang

918 total citations
8 papers, 716 citations indexed

About

Shu-Han Juang is a scholar working on Mechanical Engineering, Materials Chemistry and Civil and Structural Engineering. According to data from OpenAlex, Shu-Han Juang has authored 8 papers receiving a total of 716 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Mechanical Engineering, 2 papers in Materials Chemistry and 1 paper in Civil and Structural Engineering. Recurrent topics in Shu-Han Juang's work include Welding Techniques and Residual Stresses (6 papers), Advanced machining processes and optimization (2 papers) and Non-Destructive Testing Techniques (2 papers). Shu-Han Juang is often cited by papers focused on Welding Techniques and Residual Stresses (6 papers), Advanced machining processes and optimization (2 papers) and Non-Destructive Testing Techniques (2 papers). Shu-Han Juang collaborates with scholars based in Taiwan, Australia and United States. Shu-Han Juang's co-authors include Y.S. Tarng, Ching‐Kao Chang, Weihong Yang, Syh‐Shiuh Yeh, Yi-Ting Chen, Tetsu Yonezawa, Yichao Wu, Naratip Vittayakorn, Te‐Wei Chiu and Subramanian Sakthinathan and has published in prestigious journals such as Journal of Materials Processing Technology, The International Journal of Advanced Manufacturing Technology and Applied Sciences.

In The Last Decade

Shu-Han Juang

6 papers receiving 610 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shu-Han Juang Taiwan 5 597 171 108 86 66 8 716
A. Naveen Sait India 14 413 0.7× 162 0.9× 109 1.0× 39 0.5× 76 1.2× 32 522
Naeem Ullah Dar Pakistan 10 514 0.9× 105 0.6× 60 0.6× 258 3.0× 51 0.8× 22 562
Jorge Joaquim Pamies-teixeira Portugal 10 398 0.7× 82 0.5× 46 0.4× 122 1.4× 159 2.4× 17 548
Ching‐Kao Chang Taiwan 6 265 0.4× 138 0.8× 79 0.7× 29 0.3× 38 0.6× 9 366
E. Daniel Kirby United States 8 436 0.7× 287 1.7× 150 1.4× 27 0.3× 28 0.4× 13 547
C. M. Krishna India 9 321 0.5× 191 1.1× 109 1.0× 29 0.3× 28 0.4× 22 404
Milind Siddhpura Australia 8 408 0.7× 206 1.2× 102 0.9× 27 0.3× 22 0.3× 20 476
Mads Rostgaard Sonne Denmark 12 321 0.5× 45 0.3× 40 0.4× 125 1.5× 52 0.8× 38 473
Cem C. Tutum Denmark 14 376 0.6× 27 0.2× 35 0.3× 110 1.3× 28 0.4× 26 474

Countries citing papers authored by Shu-Han Juang

Since Specialization
Citations

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

Fields of papers citing papers by Shu-Han Juang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shu-Han Juang. 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 Shu-Han Juang. The network helps show where Shu-Han Juang may publish in the future.

Co-authorship network of co-authors of Shu-Han Juang

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

All Works

8 of 8 papers shown
1.
Juang, Shu-Han, Subramanian Sakthinathan, Tetsu Yonezawa, et al.. (2025). Preparation and Studies of ZnFe2O4–CeO2 Nanopowder via Self Combustion Glycine Nitrate Process for Methanol Steam Reforming Hydrogen Production. ACS Sustainable Resource Management. 2(8). 1416–1424.
2.
Wu, Yichao, et al.. (2023). Cross-Platform Gait Analysis and Fall Detection Wearable Device. Applied Sciences. 13(5). 3299–3299.
3.
Juang, Shu-Han & Y.S. Tarng. (2002). Process parameter selection for optimizing the weld pool geometry in the tungsten inert gas welding of stainless steel. Journal of Materials Processing Technology. 122(1). 33–37. 246 indexed citations
4.
Tarng, Y.S., Shu-Han Juang, & Ching‐Kao Chang. (2002). The use of grey-based Taguchi methods to determine submerged arc welding process parameters in hardfacing. Journal of Materials Processing Technology. 128(1-3). 1–6. 259 indexed citations
5.
Tarng, Y.S., Weihong Yang, & Shu-Han Juang. (2000). The Use of Fuzzy Logic in the Taguchi Method for the Optimisation of the Submerged Arc Welding Process. The International Journal of Advanced Manufacturing Technology. 16(9). 688–694. 104 indexed citations
6.
Tarng, Y.S., et al.. (1999). Intelligent modelling and optimization of the gas tungsten arc welding process. Journal of Intelligent Manufacturing. 10(1). 73–79. 14 indexed citations
7.
Juang, Shu-Han, et al.. (1998). A comparison between the back-propagation and counter-propagation networks in the modeling of the TIG welding process. Journal of Materials Processing Technology. 75(1-3). 54–62. 89 indexed citations
8.
Tarng, Y.S., Syh‐Shiuh Yeh, & Shu-Han Juang. (1997). Fuzzy pattern recognition of tungsten inert gas weld quality. The International Journal of Advanced Manufacturing Technology. 13(6). 387–392. 4 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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