Tim Davis
Impact in
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- Probabilistic and Robust Engineering Design
- Advanced Statistical Process Monitoring
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- Optimal Experimental Design Methods
Papers in
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- Optimal Experimental Design Methods 4
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- Advanced Statistical Process Monitoring 2
- Co-authors
- Michael S. Saccucci (1 shared paper)Dennis K. J. Lin (1 shared paper)Christopher J. Nachtsheim (1 shared paper)Jeff Jones (1 shared paper)Aaron Kite-Powell (1 shared paper)Larry Li (1 shared paper)Douglas Char (1 shared paper)Wayne Loschen (1 shared paper)
- Journals
- Technometrics (2 papers)Journal of Quality Technology (1 paper)Applied Stochastic Models in Business and Industry (1 paper)SAE technical papers on CD-ROM/SAE technical paper series (1 paper)Significance (1 paper)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Tim Davis
12 papers receiving 162 citations
Peers
Comparison fields: 5 of 72
- Statistics, Probability and Uncertainty 41
- Management Science and Operations Research 40
- Industrial and Manufacturing Engineering 24
- Statistics and Probability 19
- Software 8
Countries citing papers authored by Tim Davis
This map shows the geographic impact of Tim Davis'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 Tim Davis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Davis more than expected).
Fields of papers citing papers by Tim Davis
This network shows the impact of papers produced by Tim Davis. 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 Tim Davis. The network helps show where Tim Davis may publish in the future.
Co-authors
The 10 scholars most cited alongside Tim Davis, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1993 | 75 | |
| 2 | 2014 | 34 | |
| 3 | 2006 | 30 | |
| 4 | Divine Images: A History of Jesus on the Screen | 1992 | 21 |
| 5 | 2004 | 8 | |
| 6 | 2013 | 6 | |
| 7 | 2015 | 4 | |
| 8 | 2004 | 3 | |
| 9 | 1999 | 2 | |
| 10 | 1999 | 1 | |
| 11 | 2013 | 1 | |
| 12 | 2006 | 1 |
About Tim Davis
Tim Davis is a scholar working on Management Science and Operations Research, Statistics, Probability and Uncertainty, Statistics and Probability, Environmental Engineering and Molecular Biology, having authored 12 papers that have together received 186 indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (4 papers), Advanced Statistical Process Monitoring (2 papers), Advanced Statistical Methods and Models (2 papers), Soil Geostatistics and Mapping (2 papers), Reliability and Maintenance Optimization (1 paper), Historical and Religious Studies of Rome (1 paper), Bacillus and Francisella bacterial research (1 paper) and Software Reliability and Analysis Research (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (41 citations), Management Science and Operations Research (40 citations), Industrial and Manufacturing Engineering (24 citations), Statistics and Probability (19 citations) and Software (8 citations). Tim Davis has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Michael S. Saccucci, Dennis K. J. Lin, Christopher J. Nachtsheim, Jeff Jones, Aaron Kite-Powell, Larry Li, Douglas Char, Wayne Loschen, Janet Hamilton and John B. Henry. Their work appears in journals such as Technometrics, Journal of Quality Technology, Applied Stochastic Models in Business and Industry, SAE technical papers on CD-ROM/SAE technical paper series and Significance.
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.