Michael G. Kapteyn
Impact in
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- Digital Transformation in Industry
- Manufacturing Process and Optimization
- Health Informatics top 10%
Papers in
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- Advanced Control Systems Optimization 1
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- Probabilistic and Robust Engineering Design 3
- Co-authors
- Karen Willcox (8 shared papers)David J. Knezevic (2 shared papers)D.B.P. Huynh (1 shared paper)M. D. Tran (1 shared paper)Chengyue Wu (1 shared paper)Ernesto A. B. F. Lima (1 shared paper)David A. Hormuth (1 shared paper)Anirban Chaudhuri (1 shared paper)
- Journals
- International Journal for Numerical Methods in Engineering (2 papers)Journal of Mechanical Design (1 paper)Frontiers in Artificial Intelligence (1 paper)AIAA Scitech 2020 Forum (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (1 paper)
- Partner nations
- United StatesNew ZealandItaly
In The Last Decade
Michael G. Kapteyn
7 papers receiving 285 citations
Peers
Comparison fields: 5 of 69
- Industrial and Manufacturing Engineering 88
- Health Informatics 11
- Statistics, Probability and Uncertainty 38
- Statistical and Nonlinear Physics 46
- Medical Laboratory Technology 4
Countries citing papers authored by Michael G. Kapteyn
This map shows the geographic impact of Michael G. Kapteyn'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 Michael G. Kapteyn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael G. Kapteyn more than expected).
Fields of papers citing papers by Michael G. Kapteyn
This network shows the impact of papers produced by Michael G. Kapteyn. 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 Michael G. Kapteyn. The network helps show where Michael G. Kapteyn may publish in the future.
Co-authors
The 14 scholars most cited alongside Michael G. Kapteyn, 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 | 2020 | 144 | |
| 2 | 2020 | 76 | |
| 3 | 2023 | 51 | |
| 4 | 2022 | 10 | |
| 5 | 2019 | 5 | |
| 6 | 2025 | 2 | |
| 7 | 2018 | 1 | |
| 8 | 2024 | 0 |
About Michael G. Kapteyn
Michael G. Kapteyn is a scholar working on Control and Systems Engineering, Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics, Management Science and Operations Research and Aerospace Engineering, having authored 8 papers that have together received 289 indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (3 papers), Digital Transformation in Industry (2 papers), Risk and Portfolio Optimization (2 papers), Model Reduction and Neural Networks (2 papers), Advanced Control Systems Optimization (1 paper), Advanced Radiotherapy Techniques (1 paper), Mathematical Biology Tumor Growth (1 paper) and Spacecraft Design and Technology (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (88 citations), Health Informatics (11 citations), Statistics, Probability and Uncertainty (38 citations), Statistical and Nonlinear Physics (46 citations) and Medical Laboratory Technology (4 citations). Michael G. Kapteyn has collaborated with scholars based in United States, New Zealand and Italy. Frequent co-authors include Karen Willcox, David J. Knezevic, D.B.P. Huynh, M. D. Tran, Chengyue Wu, Ernesto A. B. F. Lima, David A. Hormuth, Anirban Chaudhuri, Guillermo Lorenzo and Thomas E. Yankeelov. Their work appears in journals such as International Journal for Numerical Methods in Engineering, Journal of Mechanical Design, Frontiers in Artificial Intelligence, AIAA Scitech 2020 Forum and DSpace@MIT (Massachusetts Institute of Technology).
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.