Patrick N. Koch

56 papers receiving 3.1k citations

Patrick N. Koch's Hit Papers

Metamodels for Computer-based Engineering Design: Survey and recommendations 2001 · 1.6k citations
1.6k0+8+16Years since publication5001k1.5k

Peers

Patrick N. Koch
Comparison fields: 5 of 111
  • Statistics, Probability and Uncertainty 649
  • Computational Theory and Mathematics 1.2k
  • Management Science and Operations Research 344
  • Management of Technology and Innovation 104
  • Artificial Intelligence 406
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Citations per field
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Citations per year

Countries citing papers authored by Patrick N. Koch

Since Specialization
Citations

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

Fields of papers citing papers by Patrick N. Koch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Patrick N. Koch. 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 Patrick N. Koch. The network helps show where Patrick N. Koch may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Metamodels for Computer-based Engineering Design: Survey and recommendations
Hit paper breakdown →
20011555
2 2004334
3 2004202
4 1997170
5 1999159
6 200276
7 200872
8 201870
9 200951
10 200048
11 201244
12 200239
13 200237
14 201530
15 201028
16 199626
17 201525
18 199420
19 201220
20 199718

About Patrick N. Koch

Patrick N. Koch is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty, Artificial Intelligence, Management Science and Operations Research and Management of Technology and Innovation, having authored 57 papers that have together received 3.3k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (22 papers), Probabilistic and Robust Engineering Design (15 papers), Machine Learning and Data Classification (9 papers), Metaheuristic Optimization Algorithms Research (6 papers), Optimal Experimental Design Methods (6 papers), Systems Engineering Methodologies and Applications (4 papers), Product Development and Customization (4 papers) and Simulation Techniques and Applications (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (649 citations), Computational Theory and Mathematics (1.2k citations), Management Science and Operations Research (344 citations), Management of Technology and Innovation (104 citations) and Artificial Intelligence (406 citations). Patrick N. Koch has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Timothy W. Simpson, Janet K. Allen, R. J. Yang, Farrokh Mistree, Linxia Gu, Wolfgang Konen, Anthony Giunta, Dipankar K. Ghosh, Andrew J. Booker and Brett A. Wujek. Their work appears in journals such as Structural and Multidisciplinary Optimization, Evolutionary Intelligence, Journal of Mechanical Design, Applied Soft Computing and Journal of Aircraft.

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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