Bi‐Min Hsu

1.3k citations
60 papers · 950 · h-index 19

Impact in

Papers in

Bi‐Min Hsu

57 papers receiving 924 citations

Peers

Bi‐Min Hsu
Comparison fields: 5 of 126
  • Statistics, Probability and Uncertainty 522
  • Statistics and Probability 187
  • Management Science and Operations Research 256
  • Industrial and Manufacturing Engineering 183
  • Medical Laboratory Technology 23
Replace Kenneth E. Case with:
Kenneth E. Case United States
Antonio Pievatolo Italy
V.N.A. Naikan India
Genbao Zhang China
V. Ebrahimipour Iran
James T. Luxhøj United States
Gary Ka Kwai Poon Hong Kong
Giacomo Maria Galante Italy
W.J. Kolarik United States
Concetta Manuela La Fata Italy
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Citations per field
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Citations per year

Countries citing papers authored by Bi‐Min Hsu

Since Specialization
Citations

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

Fields of papers citing papers by Bi‐Min Hsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bi‐Min Hsu. 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 Bi‐Min Hsu. The network helps show where Bi‐Min Hsu may publish in the future.

Co-authors

The 17 scholars most cited alongside Bi‐Min Hsu, 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 Bi‐Min Hsu Line = papers co-authored together Bi‐Min Hsu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019122
2 200761
3 200960
4 201643
5 201039
6 202032
7 202032
8 200931
9 200931
10 200530
11 202025
12 202125
13 202023
14 200722
15 202121
16 202120
17 202020
18 202218
19 200718
20 200617

About Bi‐Min Hsu

Bi‐Min Hsu is a scholar working on Statistics, Probability and Uncertainty, Management Science and Operations Research, Industrial and Manufacturing Engineering, Management Information Systems and Statistics and Probability, having authored 60 papers that have together received 950 indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (39 papers), Optimal Experimental Design Methods (14 papers), Scientific Measurement and Uncertainty Evaluation (11 papers), Industrial Vision Systems and Defect Detection (10 papers), Quality and Supply Management (9 papers), Fault Detection and Control Systems (8 papers), Multi-Criteria Decision Making (8 papers) and Reliability and Maintenance Optimization (7 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (522 citations), Statistics and Probability (187 citations), Management Science and Operations Research (256 citations), Industrial and Manufacturing Engineering (183 citations) and Medical Laboratory Technology (23 citations). Bi‐Min Hsu has collaborated with scholars based in Taiwan, Vietnam and China. Frequent co-authors include Ming‐Hung Shu, To‐Cheng Wang, Jui-Chan Huang, Thanh Lâm Nguyễn, Chien‐Wei Wu, W. L. Pearn, Binshan Lin, Kailash C. Kapur, Shuenn‐Ren Cheng and Peian Wang. Their work appears in journals such as The International Journal of Advanced Manufacturing Technology, International Journal of Production Research, Expert Systems with Applications, Materials Research Innovations and Quality Engineering.

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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