Shih‐Wen Liu
- Statistics, Probability and Uncertainty top 0.5%
- Industrial and Manufacturing Engineering top 2%
- Management Science and Operations Research top 5%
- Statistics and Probability top 5%
- Mechanical Engineering
- Topics
- Advanced Statistical Process Monitoring (21 papers)Industrial Vision Systems and Defect Detection (14 papers)Optimal Experimental Design Methods (14 papers)
- Cited by
- Statistics, Probability and UncertaintyIndustrial and Manufacturing EngineeringManagement Science and Operations Research
In The Last Decade
Shih‐Wen Liu
19 papers receiving 431 citations
Peers
Comparison fields: 5 of 20
- Statistics, Probability and Uncertainty 421
- Industrial and Manufacturing Engineering 237
- Management Science and Operations Research 212
- Statistics and Probability 109
- Mechanical Engineering 48
Countries citing papers authored by Shih‐Wen Liu
This map shows the geographic impact of Shih‐Wen Liu'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 Shih‐Wen Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shih‐Wen Liu more than expected).
Fields of papers citing papers by Shih‐Wen Liu
This network shows the impact of papers produced by Shih‐Wen Liu. 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 Shih‐Wen Liu. The network helps show where Shih‐Wen Liu may publish in the future.
Co-authorship network of co-authors of Shih‐Wen Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Shih‐Wen Liu. A scholar is included among the top collaborators of Shih‐Wen Liu 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 Shih‐Wen Liu. Shih‐Wen Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 5 | |
| 4 | 14 | |
| 5 | 7 | |
| 6 | 13 | |
| 7 | 5 | |
| 8 | 8 | |
| 9 | 7 | |
| 10 | 17 | |
| 11 | 7 | |
| 12 | 25 | |
| 13 | 27 | |
| 14 | 49 | |
| 15 | 15 | |
| 16 | 30 | |
| 17 | 36 | |
| 18 | 70 | |
| 19 | 42 | |
| 20 | 48 |
About Shih‐Wen Liu
Shih‐Wen Liu is a scholar working on Statistics, Probability and Uncertainty, Industrial and Manufacturing Engineering and Management Science and Operations Research, having authored 21 papers that have together received 431 indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (21 papers), Industrial Vision Systems and Defect Detection (14 papers) and Optimal Experimental Design Methods (14 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (421 citations), Industrial and Manufacturing Engineering (237 citations) and Management Science and Operations Research (212 citations). Shih‐Wen Liu has collaborated with scholars based in Taiwan and Indonesia. Frequent co-authors include Chien‐Wei Wu, Amy H.I. Lee, Shi‐Woei Lin, To‐Cheng Wang and Ming‐Hung Shu. Their work appears in journals such as Journal of the Operational Research Society, International Journal of Production Research and The International Journal of Advanced Manufacturing Technology.
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.