Kyle S. Hickmann
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
- Astronomy and Astrophysics top 10%
- Solar and Space Plasma Dynamics
- Ionosphere and magnetosphere dynamics
Papers in
-
- Numerical methods in inverse problems 3
- Co-authors
- James M. Hyman (5 shared papers)Sara Y. Del Valle (3 shared papers)C. N. Arge (3 shared papers)C. J. Henney (3 shared papers)Carrie A. Manore (2 shared papers)H. C. Godinez (2 shared papers)Sen Xu (1 shared paper)Helen J. Wearing (1 shared paper)
- Journals
- Inverse Problems (2 papers)ACM Transactions on Spatial Algorithms and Systems (1 paper)Solar Physics (1 paper)Space Weather (1 paper)BMC Infectious Diseases (1 paper)
- Partner nations
- United StatesItalyKenya
In The Last Decade
Kyle S. Hickmann
16 papers receiving 700 citations
Peers
Comparison fields: 5 of 102
- Modeling and Simulation 287
- Astronomy and Astrophysics 130
- Public Health, Environmental and Occupational Health 190
- Epidemiology 218
- Infectious Diseases 118
Countries citing papers authored by Kyle S. Hickmann
This map shows the geographic impact of Kyle S. Hickmann'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 Kyle S. Hickmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle S. Hickmann more than expected).
Fields of papers citing papers by Kyle S. Hickmann
This network shows the impact of papers produced by Kyle S. Hickmann. 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 Kyle S. Hickmann. The network helps show where Kyle S. Hickmann may publish in the future.
Co-authors
The 25 scholars most cited alongside Kyle S. Hickmann, 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 | 2014 | 141 | |
| 2 | 2015 | 124 | |
| 3 | 2015 | 121 | |
| 4 | 2016 | 114 | |
| 5 | 2017 | 94 | |
| 6 | 2016 | 56 | |
| 7 | 2015 | 25 | |
| 8 | 2020 | 13 | |
| 9 | 2015 | 10 | |
| 10 | 2013 | 8 | |
| 11 | 2013 | 6 | |
| 12 | 2011 | 6 | |
| 13 | 2016 | 3 | |
| 14 | 2017 | 3 | |
| 15 | 2023 | 1 | |
| 16 | 2021 | 1 | |
| 17 | 2024 | 0 | |
| 18 | 2012 | 0 |
About Kyle S. Hickmann
Kyle S. Hickmann is a scholar working on Astronomy and Astrophysics, Mathematical Physics, Epidemiology, Global and Planetary Change and Infectious Diseases, having authored 18 papers that have together received 726 indexed citations. Recurring topics across this work include Numerical methods in inverse problems (3 papers), Data-Driven Disease Surveillance (3 papers), COVID-19 epidemiological studies (2 papers), Photoacoustic and Ultrasonic Imaging (2 papers), Climate variability and models (2 papers), Influenza Virus Research Studies (2 papers), Viral Infections and Vectors (2 papers) and High-Velocity Impact and Material Behavior (2 papers). The work is most often cited by research in Modeling and Simulation (287 citations), Astronomy and Astrophysics (130 citations), Public Health, Environmental and Occupational Health (190 citations), Epidemiology (218 citations) and Infectious Diseases (118 citations). Kyle S. Hickmann has collaborated with scholars based in United States, Italy and Kenya. Frequent co-authors include James M. Hyman, Sara Y. Del Valle, C. N. Arge, C. J. Henney, Carrie A. Manore, H. C. Godinez, Sen Xu, Helen J. Wearing, Dave Osthus and Geoffrey Fairchild. Their work appears in journals such as Inverse Problems, ACM Transactions on Spatial Algorithms and Systems, Solar Physics, Space Weather and BMC Infectious Diseases.
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.