Natalie E. Sheils
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Mathematical Physics top 10%
- Advanced Mathematical Physics Problems
Papers in
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- Advanced Mathematical Physics Problems 3
-
- COVID-19 and Mental Health 3
- Co-authors
- John Buresh (8 shared papers)David A. Asch (7 shared papers)Rachel M. Werner (5 shared papers)Yong Chen (6 shared papers)Jalpa A. Doshi (4 shared papers)Bernard Deconinck (4 shared papers)David A. Smith (2 shared papers)Nazmul Islam (3 shared papers)
- Journals
- JAMA Network Open (3 papers)Journal of Physics A Mathematical and Theoretical (2 papers)BioData Mining (1 paper)The Pediatric Infectious Disease Journal (1 paper)Journal of the American Medical Informatics Association (1 paper)
- Partner nations
- United StatesVietnamSingapore
In The Last Decade
Natalie E. Sheils
21 papers receiving 484 citations
Peers
Comparison fields: 5 of 95
- Modeling and Simulation 36
- Mathematical Physics 59
- Infectious Diseases 98
- Numerical Analysis 30
- Statistical and Nonlinear Physics 52
Countries citing papers authored by Natalie E. Sheils
This map shows the geographic impact of Natalie E. Sheils'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 Natalie E. Sheils with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natalie E. Sheils more than expected).
Fields of papers citing papers by Natalie E. Sheils
This network shows the impact of papers produced by Natalie E. Sheils. 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 Natalie E. Sheils. The network helps show where Natalie E. Sheils may publish in the future.
Co-authors
The 25 scholars most cited alongside Natalie E. Sheils, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 146 | |
| 2 | 2021 | 75 | |
| 3 | 2022 | 33 | |
| 4 | 2021 | 30 | |
| 5 | 2013 | 29 | |
| 6 | 2022 | 24 | |
| 7 | 2021 | 19 | |
| 8 | 2016 | 19 | |
| 9 | 2014 | 17 | |
| 10 | 2022 | 17 | |
| 11 | 2022 | 16 | |
| 12 | 2022 | 16 | |
| 13 | 2015 | 14 | |
| 14 | 2017 | 13 | |
| 15 | 2022 | 9 | |
| 16 | 2010 | 7 | |
| 17 | 2022 | 5 | |
| 18 | 2022 | 4 | |
| 19 | 2021 | 4 | |
| 20 | 2022 | 4 |
About Natalie E. Sheils
Natalie E. Sheils is a scholar working on Mathematical Physics, Clinical Psychology, Computational Theory and Mathematics, Infectious Diseases and Numerical Analysis, having authored 22 papers that have together received 502 indexed citations. Recurring topics across this work include Advanced Mathematical Physics Problems (3 papers), COVID-19 and Mental Health (3 papers), Advanced Mathematical Modeling in Engineering (3 papers), Nonlinear Waves and Solitons (2 papers), Differential Equations and Numerical Methods (2 papers), Nonlinear Photonic Systems (1 paper), Advanced Causal Inference Techniques (1 paper) and Stability and Controllability of Differential Equations (1 paper). The work is most often cited by research in Modeling and Simulation (36 citations), Mathematical Physics (59 citations), Infectious Diseases (98 citations), Numerical Analysis (30 citations) and Statistical and Nonlinear Physics (52 citations). Natalie E. Sheils has collaborated with scholars based in United States, Vietnam and Singapore. Frequent co-authors include John Buresh, David A. Asch, Rachel M. Werner, Yong Chen, Jalpa A. Doshi, Bernard Deconinck, David A. Smith, Nazmul Islam, Ken Cohen and Chongliang Luo. Their work appears in journals such as JAMA Network Open, Journal of Physics A Mathematical and Theoretical, BioData Mining, The Pediatric Infectious Disease Journal and Journal of the American Medical Informatics Association.
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.