Benjamin D. Baugher
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
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- Mosquito-borne diseases and control
- Malaria Research and Control
- Zoonotic diseases and public health
Papers in
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- COVID-19 epidemiological studies 2
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- Anomaly Detection Techniques and Applications 2
- Explainable Artificial Intelligence (XAI) 2
- Machine Learning and Data Classification 1
- Data Stream Mining Techniques 1
- Co-authors
- Anna L. Buczak (8 shared papers)Erhan Guven (4 shared papers)Steven M. Babin (4 shared papers)Linda J. Moniz (2 shared papers)Sheri Happel Lewis (2 shared papers)Yevgeniy Elbert (2 shared papers)Jonathan Pevsner (1 shared paper)Enrique A. Tayag (1 shared paper)
- Journals
- Applied Artificial Intelligence (1 paper)BMC Genomics (1 paper)BMC Medical Informatics and Decision Making (1 paper)PLoS neglected tropical diseases (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United StatesThailandPhilippines
In The Last Decade
Benjamin D. Baugher
11 papers receiving 303 citations
Peers
Comparison fields: 5 of 78
- Modeling and Simulation 121
- Public Health, Environmental and Occupational Health 139
- Infectious Diseases 63
- Epidemiology 69
- Ecological Modeling 9
Countries citing papers authored by Benjamin D. Baugher
This map shows the geographic impact of Benjamin D. Baugher'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 Benjamin D. Baugher with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benjamin D. Baugher more than expected).
Fields of papers citing papers by Benjamin D. Baugher
This network shows the impact of papers produced by Benjamin D. Baugher. 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 Benjamin D. Baugher. The network helps show where Benjamin D. Baugher may publish in the future.
Co-authors
The 18 scholars most cited alongside Benjamin D. Baugher, 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 | 2019 | 144 | |
| 2 | 2018 | 54 | |
| 3 | 2014 | 44 | |
| 4 | 2015 | 32 | |
| 5 | 2013 | 14 | |
| 6 | 2003 | 8 | |
| 7 | 2018 | 5 | |
| 8 | 2016 | 5 | |
| 9 | 2021 | 3 | |
| 10 | 2022 | 2 | |
| 11 | 2025 | 1 |
About Benjamin D. Baugher
Benjamin D. Baugher is a scholar working on Modeling and Simulation, Artificial Intelligence, Statistical and Nonlinear Physics, Infectious Diseases and Computer Networks and Communications, having authored 11 papers that have together received 312 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (2 papers), Anomaly Detection Techniques and Applications (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Machine Learning and Data Classification (1 paper), Complex Systems and Time Series Analysis (1 paper), Data Stream Mining Techniques (1 paper), Data-Driven Disease Surveillance (1 paper) and Viral Infections and Vectors (1 paper). The work is most often cited by research in Modeling and Simulation (121 citations), Public Health, Environmental and Occupational Health (139 citations), Infectious Diseases (63 citations), Epidemiology (69 citations) and Ecological Modeling (9 citations). Benjamin D. Baugher has collaborated with scholars based in United States, Thailand and Philippines. Frequent co-authors include Anna L. Buczak, Erhan Guven, Steven M. Babin, Linda J. Moniz, Sheri Happel Lewis, Yevgeniy Elbert, Jonathan Pevsner, Enrique A. Tayag, Matthew D. Shirley and Vito G. Roque. Their work appears in journals such as Applied Artificial Intelligence, BMC Genomics, BMC Medical Informatics and Decision Making, PLoS neglected tropical diseases and Proceedings of the National Academy of Sciences.
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.