Kieran J. Sharkey
- Statistical and Nonlinear Physics top 5%
- Modeling and Simulation top 2%
- Public Health, Environmental and Occupational Health top 10%
- Nuclear and High Energy Physics top 10%
- Molecular Biology
- Co-authors
- Kenton L. MorganRoger BowersMatthew BaylisArt R. T. JonkersCraig McNeileMaya WardehRobert ChristleySusan Robinson
- Topics
- Complex Network Analysis Techniques (14 papers)COVID-19 epidemiological studies (11 papers)Mathematical and Theoretical Epidemiology and Ecology Models (11 papers)
- Partner nations
- United KingdomGermanyAustralia
In The Last Decade
Kieran J. Sharkey
35 papers receiving 680 citations
Peers
Comparison fields: 5 of 123
- Statistical and Nonlinear Physics 167
- Modeling and Simulation 167
- Public Health, Environmental and Occupational Health 139
- Nuclear and High Energy Physics 117
- Molecular Biology 113
Countries citing papers authored by Kieran J. Sharkey
This map shows the geographic impact of Kieran J. Sharkey'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 Kieran J. Sharkey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kieran J. Sharkey more than expected).
Fields of papers citing papers by Kieran J. Sharkey
This network shows the impact of papers produced by Kieran J. Sharkey. 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 Kieran J. Sharkey. The network helps show where Kieran J. Sharkey may publish in the future.
Co-authorship network of co-authors of Kieran J. Sharkey
This figure shows the co-authorship network connecting the top 25 collaborators of Kieran J. Sharkey. A scholar is included among the top collaborators of Kieran J. Sharkey based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kieran J. Sharkey. Kieran J. Sharkey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 7 | |
| 3 | 21 | |
| 4 | 4 | |
| 5 | 23 | |
| 6 | 23 | |
| 7 | 10 | |
| 8 | 8 | |
| 9 | 7 | |
| 10 | 5 | |
| 11 | 11 | |
| 12 | 19 | |
| 13 | 51 | |
| 14 | 12 | |
| 15 | 10 | |
| 16 | Exact equations for SIR epidemics on unclustered networks | 1 |
| 17 | 44 | |
| 18 | 16 | |
| 19 | 34 | |
| 20 | 94 |
About Kieran J. Sharkey
Kieran J. Sharkey is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics and Public Health, Environmental and Occupational Health, having authored 35 papers that have together received 694 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (14 papers), COVID-19 epidemiological studies (11 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (11 papers). The work is most often cited by research in Modeling and Simulation (167 citations), Statistical and Nonlinear Physics (167 citations) and Nuclear and High Energy Physics (117 citations). Kieran J. Sharkey has collaborated with scholars based in United Kingdom, Germany and Australia. Frequent co-authors include Kenton L. Morgan, Roger Bowers, Matthew Baylis, Art R. T. Jonkers, Craig McNeile, Maya Wardeh, Robert Christley, Susan Robinson, Emily G. Armitage and Kaye J. Williams. Their work appears in journals such as Journal of Biological Chemistry, Nature Communications and PLoS ONE.
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.