Andrew Glaws
Impact in
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- Meteorological Phenomena and Simulations
Papers in
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- Probabilistic and Robust Engineering Design 8
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- Model Reduction and Neural Networks 10
- Co-authors
- Ryan N. King (17 shared papers)Dylan Hettinger (1 shared paper)Michael Sprague (1 shared paper)Dylan Harrison‐Atlas (5 shared papers)Paul G. Constantine (3 shared papers)Ganesh Vijayakumar (4 shared papers)Grant Buster (4 shared papers)Eric J. Lantz (1 shared paper)
- Journals
- Nature Energy (3 papers)AIAA Journal (2 papers)Solar RRL (2 papers)Applied Energy (2 papers)Wind Energy (2 papers)
- Partner nations
- United StatesGermanyChina
In The Last Decade
Andrew Glaws
31 papers receiving 419 citations
Peers
Comparison fields: 5 of 70
- Computational Mathematics 4
- Atmospheric Science 95
- Statistical and Nonlinear Physics 62
- Environmental Engineering 65
- Statistics, Probability and Uncertainty 27
Countries citing papers authored by Andrew Glaws
This map shows the geographic impact of Andrew Glaws'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 Andrew Glaws with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Glaws more than expected).
Fields of papers citing papers by Andrew Glaws
This network shows the impact of papers produced by Andrew Glaws. 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 Andrew Glaws. The network helps show where Andrew Glaws may publish in the future.
Co-authors
The 25 scholars most cited alongside Andrew Glaws, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 173 | |
| 2 | 2020 | 40 | |
| 3 | 2024 | 25 | |
| 4 | 2024 | 25 | |
| 5 | 2022 | 20 | |
| 6 | 2020 | 20 | |
| 7 | 2023 | 16 | |
| 8 | 2021 | 13 | |
| 9 | 2017 | 13 | |
| 10 | 2024 | 12 | |
| 11 | 2019 | 11 | |
| 12 | 2020 | 10 | |
| 13 | 2025 | 7 | |
| 14 | 2023 | 6 | |
| 15 | 2022 | 5 | |
| 16 | 2020 | 4 | |
| 17 | 2022 | 3 | |
| 18 | 2020 | 3 | |
| 19 | 2025 | 3 | |
| 20 | 2025 | 3 |
About Andrew Glaws
Andrew Glaws is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics, Aerospace Engineering, Computational Mechanics and Computational Theory and Mathematics, having authored 36 papers that have together received 428 indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (10 papers), Probabilistic and Robust Engineering Design (8 papers), Wind Energy Research and Development (7 papers), Advanced Multi-Objective Optimization Algorithms (4 papers), Energy Load and Power Forecasting (4 papers), Wind and Air Flow Studies (4 papers), Solar Radiation and Photovoltaics (3 papers) and Perovskite Materials and Applications (3 papers). The work is most often cited by research in Computational Mathematics (4 citations), Atmospheric Science (95 citations), Statistical and Nonlinear Physics (62 citations), Environmental Engineering (65 citations) and Statistics, Probability and Uncertainty (27 citations). Andrew Glaws has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Ryan N. King, Dylan Hettinger, Michael Sprague, Dylan Harrison‐Atlas, Paul G. Constantine, Ganesh Vijayakumar, Grant Buster, Eric J. Lantz, Shreyas Ananthan and Sakshi Mishra. Their work appears in journals such as Nature Energy, AIAA Journal, Solar RRL, Applied Energy and Wind Energy.
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.