G. M. Kepler
Impact in
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- Electrostatics and Colloid Interactions
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- Model Reduction and Neural Networks
Papers in
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- Model Reduction and Neural Networks 4
- Co-authors
- Seth Fraden (1 shared paper)Julia S. Kimbell (3 shared papers)H. T. Banks (8 shared papers)Rebecca Segal (1 shared paper)Hien Tran (5 shared papers)Regina B. Richardson (2 shared papers)Kevin T. Morgan (2 shared papers)Marie Davidian (2 shared papers)
- Journals
- Mathematical and Computer Modelling (3 papers)SIAM Journal on Applied Mathematics (2 papers)Optimal Control Applications and Methods (2 papers)Annals of Biomedical Engineering (1 paper)IEEE Transactions on Semiconductor Manufacturing (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
G. M. Kepler
18 papers receiving 559 citations
Peers
Comparison fields: 5 of 102
- Physical and Theoretical Chemistry 191
- Statistical and Nonlinear Physics 79
- Sensory Systems 29
- Process Chemistry and Technology 16
- Virology 22
Countries citing papers authored by G. M. Kepler
This map shows the geographic impact of G. M. Kepler'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 G. M. Kepler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. M. Kepler more than expected).
Fields of papers citing papers by G. M. Kepler
This network shows the impact of papers produced by G. M. Kepler. 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 G. M. Kepler. The network helps show where G. M. Kepler may publish in the future.
Co-authors
The 21 scholars most cited alongside G. M. Kepler, 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 | 1994 | 278 | |
| 2 | 2008 | 75 | |
| 3 | 1998 | 68 | |
| 4 | 2008 | 46 | |
| 5 | 2002 | 30 | |
| 6 | 2000 | 26 | |
| 7 | 1995 | 24 | |
| 8 | 2008 | 18 | |
| 9 | 2001 | 8 | |
| 10 | 2006 | 7 | |
| 11 | 2000 | 5 | |
| 12 | 1999 | 4 | |
| 13 | 1998 | 4 | |
| 14 | 2007 | 2 | |
| 15 | 2009 | 1 | |
| 16 | 2003 | 1 | |
| 17 | 1997 | 1 | |
| 18 | 2003 | 1 |
About G. M. Kepler
G. M. Kepler is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics, Aerospace Engineering, Statistics, Probability and Uncertainty and Biomedical Engineering, having authored 18 papers that have together received 599 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (4 papers), Nuclear reactor physics and engineering (3 papers), HIV Research and Treatment (2 papers), Electromagnetic Simulation and Numerical Methods (2 papers), Electromagnetic Scattering and Analysis (2 papers), Probabilistic and Robust Engineering Design (2 papers), Advanced Chemical Sensor Technologies (1 paper) and Electrostatics and Colloid Interactions (1 paper). The work is most often cited by research in Physical and Theoretical Chemistry (191 citations), Statistical and Nonlinear Physics (79 citations), Sensory Systems (29 citations), Process Chemistry and Technology (16 citations) and Virology (22 citations). G. M. Kepler has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Seth Fraden, Julia S. Kimbell, H. T. Banks, Rebecca Segal, Hien Tran, Regina B. Richardson, Kevin T. Morgan, Marie Davidian, Shuhua Hu and Eli S. Rosenberg. Their work appears in journals such as Mathematical and Computer Modelling, SIAM Journal on Applied Mathematics, Optimal Control Applications and Methods, Annals of Biomedical Engineering and IEEE Transactions on Semiconductor Manufacturing.
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.