John A. Cafeo

1.5k total citations · 1 hit paper
28 papers, 1.0k citations indexed

About

John A. Cafeo is a scholar working on Mechanical Engineering, Civil and Structural Engineering and Artificial Intelligence. According to data from OpenAlex, John A. Cafeo has authored 28 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Mechanical Engineering, 10 papers in Civil and Structural Engineering and 5 papers in Artificial Intelligence. Recurrent topics in John A. Cafeo's work include Structural Health Monitoring Techniques (7 papers), Probabilistic and Robust Engineering Design (5 papers) and Manufacturing Process and Optimization (5 papers). John A. Cafeo is often cited by papers focused on Structural Health Monitoring Techniques (7 papers), Probabilistic and Robust Engineering Design (5 papers) and Manufacturing Process and Optimization (5 papers). John A. Cafeo collaborates with scholars based in United States, India and Poland. John A. Cafeo's co-authors include James C. Cavendish, Marc C. Kennedy, Dave Higdon, Robert D. Ryne, James O. Berger, Rui Paulo, J. Sacks, M. J. Bayarri, Jian Tu and Martin W. Trethewey and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Computer Methods in Applied Mechanics and Engineering.

In The Last Decade

John A. Cafeo

24 papers receiving 935 citations

Hit Papers

A Framework for Validation of Computer Models 2007 2026 2013 2019 2007 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
John A. Cafeo United States 7 489 356 205 197 119 28 1.0k
James Gattiker United States 12 394 0.8× 284 0.8× 247 1.2× 162 0.8× 86 0.7× 26 1.1k
Olivier Roustant France 16 571 1.2× 589 1.7× 326 1.6× 348 1.8× 167 1.4× 52 1.3k
Amandine Marrel France 15 509 1.0× 274 0.8× 128 0.6× 157 0.8× 148 1.2× 38 934
J. Sacks United States 12 408 0.8× 279 0.8× 156 0.8× 230 1.2× 66 0.6× 17 900
Fabrice Gamboa France 19 486 1.0× 176 0.5× 160 0.8× 112 0.6× 182 1.5× 79 1.3k
Xun Huan United States 15 362 0.7× 203 0.6× 165 0.8× 143 0.7× 117 1.0× 69 1.1k
Nathalie Bartoli France 16 386 0.8× 544 1.5× 135 0.7× 200 1.0× 94 0.8× 69 1.1k
Jason L. Loeppky Canada 13 265 0.5× 395 1.1× 131 0.6× 348 1.8× 125 1.1× 30 990
Davide Serafini United States 3 205 0.4× 437 1.2× 150 0.7× 147 0.7× 63 0.5× 6 772
John Jakeman United States 21 664 1.4× 253 0.7× 116 0.6× 92 0.5× 224 1.9× 57 1.2k

Countries citing papers authored by John A. Cafeo

Since Specialization
Citations

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

Fields of papers citing papers by John A. Cafeo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John A. Cafeo

This figure shows the co-authorship network connecting the top 25 collaborators of John A. Cafeo. A scholar is included among the top collaborators of John A. Cafeo 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 John A. Cafeo. John A. Cafeo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rajpathak, Dnyanesh & John A. Cafeo. (2021). A Semantic Similarity Model to Compare Heterogeneous Data Sources to Augment Engineering Data with New Failure modes in Automotive Industry. PHM Society European Conference. 6(1). 10–10.
2.
Cafeo, John A., et al.. (2020). Customer Perception of Road-Induced Structural Feel. SAE technical papers on CD-ROM/SAE technical paper series. 1. 2 indexed citations
3.
Takai, Shun, et al.. (2011). A Bayesian Method for Predicting Future Customer Need Distributions. Concurrent Engineering. 19(3). 255–264. 3 indexed citations
4.
Takai, Shun, et al.. (2010). A Bayesian Framework for Predicting Cutomer Need Distributions. 193–203. 2 indexed citations
5.
Bayarri, M. J., James O. Berger, Marc C. Kennedy, et al.. (2009). Predicting Vehicle Crashworthiness: Validation of Computer Models for Functional and Hierarchical Data. Journal of the American Statistical Association. 104(487). 929–943. 26 indexed citations
6.
Raghavan, N. R. Srinivasa & John A. Cafeo. (2009). Product Research. Durham Research Online (Durham University). 1 indexed citations
7.
Rebba, Ramesh & John A. Cafeo. (2007). Probabilistic analysis of a static frame model. Computer Methods in Applied Mechanics and Engineering. 197(29-32). 2561–2571. 5 indexed citations
8.
Bayarri, M. J., James O. Berger, Rui Paulo, et al.. (2007). A Framework for Validation of Computer Models. Technometrics. 49(2). 138–154. 456 indexed citations breakdown →
9.
Morgan, Alexander P., et al.. (2005). The General-Motors Variation-Reduction Adviser. AI Magazine. 26(3). 19–28. 4 indexed citations
10.
Morgan, Alexander P., et al.. (2004). The general motors variation-reduction adviser: deployment issues for an AI application. 26(3). 777–784. 3 indexed citations
11.
Cafeo, John A., et al.. (2001). Capturing Lessons Learned for Variation Reduction in an Automotive Assembly Plant. The Florida AI Research Society. 89–92. 5 indexed citations
12.
Cafeo, John A., et al.. (1998). Considerations to reduce modal analysis test variability. 3243. 470–476. 4 indexed citations
13.
Cafeo, John A., et al.. (1997). A Design-of-experiments Approach to Quantifying Test-to-test Variability for a Modal Test. Proceedings of SPIE, the International Society for Optical Engineering. 3089. 598–604. 11 indexed citations
14.
Sommer, H. J., Michael A. Erickson, Martin W. Trethewey, & John A. Cafeo. (1994). Single-beam Laser Vibrometer for Simultaneous Measurement of Translation Pitch and Roll with Neural Network Calibration. 2251. 1196.
15.
Trethewey, Martin W., H. J. Sommer, & John A. Cafeo. (1993). A Dual Beam Laser Vibrometer for Measurement of Dynamic Structural Rotations and Displacements. Journal of Sound and Vibration. 164(1). 67–84. 14 indexed citations
16.
Cafeo, John A., Martin W. Trethewey, & H. J. Sommer. (1993). On the use of measured rotational degrees of freedom in structural dynamics modification. 96–101.
17.
Cafeo, John A., Martin W. Trethewey, & H. J. Sommer. (1992). Measurement and application of experimental rotational degrees of freedom for mode shape refinement. 7(4). 255–269. 3 indexed citations
18.
Trethewey, Martin W. & John A. Cafeo. (1992). Tutorial. Signal processing aspects of structural impact testing. 7(2). 129–149. 9 indexed citations
19.
Cafeo, John A., et al.. (1991). Application of a three degree of freedom laser vibrometer for experimental modal analysis. 2. 1161–1167. 1 indexed citations
20.
Trethewey, Martin W. & John A. Cafeo. (1987). Experimental Acoustic Field Characterization of Enclosures by Impedance Estimates and Modal Analysis. Journal of vibration and acoustics. 109(4). 388–396. 1 indexed citations

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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