J. Gani
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
- Statistics and Probability top 0.5%
- Statistical Distribution Estimation and Applications
Papers in
-
- Stochastic processes and statistical mechanics 44
-
- COVID-19 epidemiological studies 35
- Co-authors
- Sheldon M. Ross (1 shared paper)D. J. Daley (5 shared papers)Derek A. Zelmer (1 shared paper)John W. Van Ness (1 shared paper)F. N. David (1 shared paper)Peter J. Brockwell (4 shared papers)Sidney I. Resnick (3 shared papers)D. Jerwood (3 shared papers)
- Journals
- Journal of Applied Probability (40 papers)Advances in Applied Probability (10 papers)Biometrika (7 papers)Biometrics (5 papers)Journal of the American Statistical Association (5 papers)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
J. Gani
149 papers receiving 3.8k citations
J. Gani's Hit Papers
Peers
Comparison fields: 5 of 171
- Modeling and Simulation 491
- Statistics and Probability 770
- Management Information Systems 731
- Mathematical Physics 558
- Software 226
Countries citing papers authored by J. Gani
This map shows the geographic impact of J. Gani'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 J. Gani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Gani more than expected).
Fields of papers citing papers by J. Gani
This network shows the impact of papers produced by J. Gani. 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 J. Gani. The network helps show where J. Gani may publish in the future.
Co-authors
The 25 scholars most cited alongside J. Gani, 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 160 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Applied Probability Models with Optimization Applications. Hit paper breakdown → | 1971 | 1684 |
| 2 | 2000 | 409 | |
| 3 | 1984 | 215 | |
| 4 | 1980 | 196 | |
| 5 | 1967 | 159 | |
| 6 | 1982 | 121 | |
| 7 | 1963 | 107 | |
| 8 | 1974 | 81 | |
| 9 | 1957 | 70 | |
| 10 | 1972 | 47 | |
| 11 | 1972 | 45 | |
| 12 | 1968 | 38 | |
| 13 | 1965 | 36 | |
| 14 | 1963 | 35 | |
| 15 | 1969 | 33 | |
| 16 | 1971 | 33 | |
| 17 | 1960 | 32 | |
| 18 | 1978 | 29 | |
| 19 | 1984 | 27 | |
| 20 | 2001 | 25 |
About J. Gani
J. Gani is a scholar working on Mathematical Physics, Modeling and Simulation, Public Health, Environmental and Occupational Health, Statistics and Probability and Artificial Intelligence, having authored 160 papers that have together received 4.3k indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (44 papers), COVID-19 epidemiological studies (35 papers), Mathematical and Theoretical Epidemiology and Ecology Models (28 papers), Bayesian Methods and Mixture Models (12 papers), Evolution and Genetic Dynamics (11 papers), Probability and Risk Models (11 papers), Advanced Queuing Theory Analysis (10 papers) and Stochastic processes and financial applications (7 papers). The work is most often cited by research in Modeling and Simulation (491 citations), Statistics and Probability (770 citations), Management Information Systems (731 citations), Mathematical Physics (558 citations) and Software (226 citations). J. Gani has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Sheldon M. Ross, D. J. Daley, Derek A. Zelmer, John W. Van Ness, F. N. David, Peter J. Brockwell, Sidney I. Resnick, D. Jerwood, J. H. Pollard and N. U. Prabhu. Their work appears in journals such as Journal of Applied Probability, Advances in Applied Probability, Biometrika, Biometrics and Journal of the American Statistical 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.