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

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A Framework for Validation of Computer Models

2007 456 citations M. J. Bayarri, James O. Berger et al. Technometrics profile →

Peers

John A. Cafeo

SPU

CTM

AI

MSOR

CSE

James Gattiker United States

Olivier Roustant France

Amandine Marrel France

J. Sacks United States

Fabrice Gamboa France

Xun Huan United States

Nathalie Bartoli France

Jason L. Loeppky Canada

Davide Serafini United States

John Jakeman United States

James Gattiker United States

John A. Cafeo

394 ×0.8

SPU

284 ×0.8

CTM

247 ×1.2

AI

162 ×0.8

MSOR

86 ×0.7

CSE

Citations per year, relative to John A. Cafeo John A. Cafeo (= 1×) peers James Gattiker

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

Sort: Min cites: Since: Top N: Style:

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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