John S. Usher

1.6k citations
59 papers · 1.2k · h-index 20

Impact in

Papers in

John S. Usher

57 papers receiving 1.1k citations

Peers

John S. Usher
Comparison fields: 5 of 88
  • Statistics, Probability and Uncertainty 402
  • Statistics and Probability 455
  • Safety, Risk, Reliability and Quality 447
  • Software 100
  • Industrial and Manufacturing Engineering 235
Replace Yu Zhao with:
Yu Zhao China
Jeffrey P. Kharoufeh United States
Xufeng Zhao China
Laurence Dieulle France
Tieling Zhang Australia
V.N.A. Naikan India
Yisha Xiang United States
Éric Levrat France
Jørn Vatn Norway
Rosmaini Ahmad Malaysia
John S. Usher relative to Yu Zhao China Yu Zhao's profile →
Citations per field
00.5×2.7×
Yu Zhao · 1×
Citations per year

Countries citing papers authored by John S. Usher

Since Specialization
Citations

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

Fields of papers citing papers by John S. Usher

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John S. Usher. 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 John S. Usher. The network helps show where John S. Usher may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011117
2 198891
3 201184
4 199159
5 199557
6 199553
7 199351
8 199651
9 200745
10
199842
11 199642
12 201140
13 199538
14 199837
15 200235
16 201028
17 201027
18 200727
19 198926
20 200122

About John S. Usher

John S. Usher is a scholar working on Safety, Risk, Reliability and Quality, Statistics, Probability and Uncertainty, Statistics and Probability, Industrial and Manufacturing Engineering and Software, having authored 59 papers that have together received 1.2k indexed citations. Recurring topics across this work include Reliability and Maintenance Optimization (23 papers), Statistical Distribution Estimation and Applications (14 papers), Software Reliability and Analysis Research (12 papers), Probabilistic and Robust Engineering Design (9 papers), Hearing Loss and Rehabilitation (8 papers), Speech and Audio Processing (6 papers), Advanced Manufacturing and Logistics Optimization (4 papers) and Manufacturing Process and Optimization (4 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (402 citations), Statistics and Probability (455 citations), Safety, Risk, Reliability and Quality (447 citations), Software (100 citations) and Industrial and Manufacturing Engineering (235 citations). John S. Usher has collaborated with scholars based in United States, Canada and Israel. Frequent co-authors include Kamran S. Moghaddam, Frank M. Guess, Thom J. Hodgson, Dennis K. J. Lin, Thomas L. Starr, G. Don Taylor, Irwin Guttman, Benjamin Reiser, Jacob Benesty and Gail W. DePuy. Their work appears in journals such as IEEE Transactions on Reliability, Computers & Industrial Engineering, Quality and Reliability Engineering International, Journal of the Audio Engineering Society 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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