Philip D. O’Neill
Impact in
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies
- Statistics and Probability top 2%
- Statistical Methods and Bayesian Inference
Papers in
-
- COVID-19 epidemiological studies 46
-
- Statistical Methods and Bayesian Inference 14
- Co-authors
- Gareth O. RobertsFrank BallTom BrittonNikolaos DemirisTheodore KypraiosDamian ClancyC. S. NicolNiels G. Becker
- Journals
- Advances in Applied Probability (8 papers)Journal of Applied Probability (8 papers)Biostatistics (6 papers)Mathematical Biosciences (5 papers)Scandinavian Journal of Statistics (5 papers)
- Partner nations
- United KingdomUnited StatesThailand
In The Last Decade
Philip D. O’Neill
73 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 121
- Modeling and Simulation 818
- Statistics and Probability 249
- Agronomy and Crop Science 168
- Public Health, Environmental and Occupational Health 423
- Infectious Diseases 259
Countries citing papers authored by Philip D. O’Neill
This map shows the geographic impact of Philip D. O’Neill'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 Philip D. O’Neill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip D. O’Neill more than expected).
Fields of papers citing papers by Philip D. O’Neill
This network shows the impact of papers produced by Philip D. O’Neill. 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 Philip D. O’Neill. The network helps show where Philip D. O’Neill may publish in the future.
Co-authors
The 25 scholars most cited alongside Philip D. O’Neill, 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 | 2016 | 39 | |
| 2 | 2016 | 17 | |
| 3 | 2013 | 38 | |
| 4 | 2013 | 9 | |
| 5 | 2012 | 2 | |
| 6 | 2011 | 1 | |
| 7 | 2010 | 58 | |
| 8 | 2010 | 47 | |
| 9 | 2010 | 49 | |
| 10 | 2009 | 1 | |
| 11 | 2008 | 17 | |
| 12 | 2007 | 5 | |
| 13 | 2007 | 22 | |
| 14 | 2007 | 1 | |
| 15 | 2003 | 17 | |
| 16 | 2003 | 15 | |
| 17 | 2001 | 36 | |
| 18 | 1998 | 2 | |
| 19 | 1991 | 53 | |
| 20 | 1976 | 11 |
About Philip D. O’Neill
Philip D. O’Neill is a scholar working on Modeling and Simulation, Statistics and Probability, Mathematical Physics, Public Health, Environmental and Occupational Health and Clinical Biochemistry, having authored 78 papers that have together received 1.7k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (46 papers), Mathematical and Theoretical Epidemiology and Ecology Models (26 papers), Statistical Methods and Bayesian Inference (14 papers), Stochastic processes and statistical mechanics (12 papers), Bayesian Methods and Mixture Models (9 papers), Influenza Virus Research Studies (8 papers), Complex Network Analysis Techniques (6 papers) and Evolution and Genetic Dynamics (5 papers). The work is most often cited by research in Modeling and Simulation (818 citations), Statistics and Probability (249 citations), Agronomy and Crop Science (168 citations), Public Health, Environmental and Occupational Health (423 citations) and Infectious Diseases (259 citations). Philip D. O’Neill has collaborated with scholars based in United Kingdom, United States and Thailand. Frequent co-authors include Gareth O. Roberts, Frank Ball, Tom Britton, Nikolaos Demiris, Theodore Kypraios, Damian Clancy, C. S. Nicol, Niels G. Becker, John A. Jacquez and Ben S. Cooper. Their work appears in journals such as Advances in Applied Probability, Journal of Applied Probability, Biostatistics, Mathematical Biosciences and Scandinavian Journal of Statistics.
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.