Shing I. Chang

2.0k citations
60 papers · 1.6k indexed · h-index 23

Impact in

Papers in

Shing I. Chang

60 papers receiving 1.5k citations

Peers

Shing I. Chang
Comparison fields: 5 of 134
  • Statistics, Probability and Uncertainty 351
  • Industrial and Manufacturing Engineering 356
  • Statistics and Probability 228
  • Management Science and Operations Research 313
  • Automotive Engineering 252
Replace Genbao Zhang with:
Genbao Zhang China
Soumaya Yacout Canada
Massimo Pacella Italy
Aart van Harten Netherlands
Madhu Jain India
Hong‐Zhong Huang China
Lin Lin China
Jinhua Mi China
Ershun Pan China
Pratyush Sen United Kingdom
Shing I. Chang relative to Genbao Zhang China Genbao Zhang's profile →
Citations per field
00.5×8.3×
Genbao Zhang · 1×
Citations per year

Countries citing papers authored by Shing I. Chang

Since Specialization
Citations

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

Fields of papers citing papers by Shing I. Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shing I. 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 Shing I. Chang. The network helps show where Shing I. Chang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20248
3 20232
4 20202
5 20187
6 20179
7 20152
8 20146
9 201464
10 201324
11 201218
12 20121
13 200836
14 20081
15 200714
16 200265
17 199954
18 199673
19 199421
20 19903

About Shing I. Chang

Shing I. Chang is a scholar working on Statistics, Probability and Uncertainty, Industrial and Manufacturing Engineering, Statistics and Probability, Management Science and Operations Research and Medical Laboratory Technology, having authored 60 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (21 papers), Manufacturing Process and Optimization (14 papers), Fault Detection and Control Systems (11 papers), Scientific Measurement and Uncertainty Evaluation (7 papers), Advanced Statistical Methods and Models (7 papers), Industrial Vision Systems and Defect Detection (7 papers), Optimal Experimental Design Methods (7 papers) and Advanced Multi-Objective Optimization Algorithms (5 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (351 citations), Industrial and Manufacturing Engineering (356 citations), Statistics and Probability (228 citations), Management Science and Operations Research (313 citations) and Automotive Engineering (252 citations). Shing I. Chang has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Young-Jou Lai, Shuting Lei, Tzong‐Ru Tsai, Edmond S. L. Ho, Behnam Malmir, Tarik Aouam, Jianfeng Ma, Youping Deng, E. Stanley Lee and Susan J. Brown. Their work appears in journals such as Computers & Industrial Engineering, International Journal of Production Research, Quality Engineering, The International Journal of Advanced Manufacturing Technology and International Journal of Lean Six Sigma.

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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