Andrew D. Barbour
- Mathematical Physics top 5%
- Public Health, Environmental and Occupational Health top 10%
- Statistics and Probability top 2%
- Molecular Biology
- Genetics
- Co-authors
- Robert D. MartínAihua XiaLouis H. Y. ChenGesine ReinertRob J. de BoerSebastian BonhoefferAndrea PuglieseToby Hulf
- Topics
- Stochastic processes and statistical mechanics (19 papers)COVID-19 epidemiological studies (9 papers)Bayesian Methods and Mixture Models (9 papers)
- Partner nations
- SwitzerlandUnited KingdomUnited States
In The Last Decade
Andrew D. Barbour
47 papers receiving 927 citations
Peers
Comparison fields: 5 of 124
- Mathematical Physics 196
- Public Health, Environmental and Occupational Health 186
- Statistics and Probability 182
- Molecular Biology 152
- Genetics 139
Countries citing papers authored by Andrew D. Barbour
This map shows the geographic impact of Andrew D. Barbour'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 Andrew D. Barbour with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew D. Barbour more than expected).
Fields of papers citing papers by Andrew D. Barbour
This network shows the impact of papers produced by Andrew D. Barbour. 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 Andrew D. Barbour. The network helps show where Andrew D. Barbour may publish in the future.
Co-authorship network of co-authors of Andrew D. Barbour
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew D. Barbour. A scholar is included among the top collaborators of Andrew D. Barbour 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 Andrew D. Barbour. Andrew D. Barbour is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 2 | |
| 4 | 28 | |
| 5 | 4 | |
| 6 | 7 | |
| 7 | 6 | |
| 8 | 18 | |
| 9 | 6 | |
| 10 | 6 | |
| 11 | 64 | |
| 12 | 50 | |
| 13 | 42 | |
| 14 | 42 | |
| 15 | 73 | |
| 16 | 81 | |
| 17 | 13 | |
| 18 | 55 | |
| 19 | 4 | |
| 20 | 17 |
About Andrew D. Barbour
Andrew D. Barbour is a scholar working on Mathematical Physics, Modeling and Simulation and Statistics and Probability, having authored 48 papers that have together received 993 indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (19 papers), COVID-19 epidemiological studies (9 papers) and Bayesian Methods and Mixture Models (9 papers). The work is most often cited by research in Modeling and Simulation (119 citations), Statistics and Probability (182 citations) and Mathematical Physics (196 citations). Andrew D. Barbour has collaborated with scholars based in Switzerland, United Kingdom and United States. Frequent co-authors include Robert D. Martín, Aihua Xia, Louis H. Y. Chen, Gesine Reinert, Rob J. de Boer, Sebastian Bonhoeffer, Andrea Pugliese, Toby Hulf, Paola Bellosta and Peter Gallant. Their work appears in journals such as Nature Communications, Molecular and Cellular Biology and Applied and Environmental Microbiology.
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.