John E. Renaud

6.4k citations
166 papers · 5.4k · h-index 41

Impact in

Papers in

John E. Renaud

163 papers receiving 5.1k citations

Peers

John E. Renaud
Comparison fields: 5 of 130
  • Statistics, Probability and Uncertainty 1.9k
  • Computational Theory and Mathematics 2.5k
  • Industrial and Manufacturing Engineering 913
  • Automotive Engineering 1.0k
  • Management Science and Operations Research 990
Replace G. Gary Wang with:
G. Gary Wang Canada
Xinyu Shao China
Byeng D. Youn South Korea
Ping Jiang China
R. J. Yang United States
Zhen Hu United States
Hong‐Zhong Huang China
Gengdong Cheng China
Xiaoping Du United States
Sujin Bureerat Thailand
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Citations per field
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Citations per year

Countries citing papers authored by John E. Renaud

Since Specialization
Citations

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

Fields of papers citing papers by John E. Renaud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 166 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001318
2 2003288
3 2004280
4 2000189
5 1997162
6 2005138
7 2006137
8 1996134
9 1997131
10 2009129
11 2003128
12 2000127
13 2006116
14 1998114
15 2000111
16 199898
17 199394
18 199689
19 199489
20 200082

About John E. Renaud

John E. Renaud is a scholar working on Computational Theory and Mathematics, Civil and Structural Engineering, Statistics, Probability and Uncertainty, Management Science and Operations Research and Mechanical Engineering, having authored 166 papers that have together received 5.4k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (83 papers), Topology Optimization in Engineering (55 papers), Probabilistic and Robust Engineering Design (54 papers), Optimal Experimental Design Methods (29 papers), Manufacturing Process and Optimization (21 papers), Structural Analysis and Optimization (14 papers), Advanced Optimization Algorithms Research (11 papers) and Advanced Mathematical Modeling in Engineering (10 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (1.9k citations), Computational Theory and Mathematics (2.5k citations), Industrial and Manufacturing Engineering (913 citations), Automotive Engineering (1.0k citations) and Management Science and Operations Research (990 citations). John E. Renaud has collaborated with scholars based in United States, Colombia and Venezuela. Frequent co-authors include James P. Thomas, José F. Rodrı́guez, Ravindra V. Tappeta, Harish Agarwal, Stephen M. Batill, Shawn Gano, Andrés Tovar, Gary A. Gabriele, Neal Patel and Brett Wujek. Their work appears in journals such as AIAA Journal, Journal of Mechanical Design, Engineering Optimization, Structural and Multidisciplinary Optimization and SAE technical papers on CD-ROM/SAE technical paper series.

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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