Jonathan Hennessy
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Transportation top 10%
- Human Mobility and Location-Based Analysis
Papers in
-
- COVID-19 epidemiological studies 4
-
- Statistical Methods and Bayesian Inference 3
- Statistical Methods in Clinical Trials 2
- Statistical Methods and Inference 2
- Co-authors
- Mark E. Glickman (3 shared papers)Cassandra Wolos Pattanayak (2 shared papers)Tirthankar Dasgupta (2 shared papers)Luke W Miratrix (2 shared papers)Evgeniy Gabrilovich (1 shared paper)Liana Woskie (1 shared paper)Thomas C. Tsai (1 shared paper)Katie O’Connor (1 shared paper)
- Journals
- Journal of Quantitative Analysis in Sports (2 papers)Health Services Research (1 paper)Journal of Causal Inference (1 paper)PLoS ONE (1 paper)DOAJ (DOAJ: Directory of Open Access Journals) (1 paper)
- Partner nations
- United StatesIrelandItaly
In The Last Decade
Jonathan Hennessy
10 papers receiving 190 citations
Peers
Comparison fields: 5 of 61
- Modeling and Simulation 74
- Transportation 34
- Statistics and Probability 24
- Health 15
- Economics and Econometrics 46
Countries citing papers authored by Jonathan Hennessy
This map shows the geographic impact of Jonathan Hennessy'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 Jonathan Hennessy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Hennessy more than expected).
Fields of papers citing papers by Jonathan Hennessy
This network shows the impact of papers produced by Jonathan Hennessy. 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 Jonathan Hennessy. The network helps show where Jonathan Hennessy may publish in the future.
Co-authors
The 15 scholars most cited alongside Jonathan Hennessy, 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 | 2021 | 76 | |
| 2 | 2021 | 39 | |
| 3 | Impacts of State-Level Policies on Social Distancing in the United States Using Aggregated Mobility Data during the COVID-19 Pandemic | 2020 | 32 |
| 4 | 2016 | 20 | |
| 5 | 2015 | 16 | |
| 6 | 2015 | 9 | |
| 7 | 2018 | 2 | |
| 8 | 2021 | 2 | |
| 9 | 2016 | 1 | |
| 10 | 2020 | 1 |
About Jonathan Hennessy
Jonathan Hennessy is a scholar working on Modeling and Simulation, Statistics and Probability, Health, Economics and Econometrics and Information Systems, having authored 10 papers that have together received 198 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (4 papers), Sports Analytics and Performance (3 papers), Statistical Methods and Bayesian Inference (3 papers), Statistical Methods in Clinical Trials (2 papers), Statistical Methods and Inference (2 papers), Health disparities and outcomes (2 papers), Software Engineering Research (1 paper) and Economic and Environmental Valuation (1 paper). The work is most often cited by research in Modeling and Simulation (74 citations), Transportation (34 citations), Statistics and Probability (24 citations), Health (15 citations) and Economics and Econometrics (46 citations). Jonathan Hennessy has collaborated with scholars based in United States, Ireland and Italy. Frequent co-authors include Mark E. Glickman, Cassandra Wolos Pattanayak, Tirthankar Dasgupta, Luke W Miratrix, Evgeniy Gabrilovich, Liana Woskie, Thomas C. Tsai, Katie O’Connor, Melissa S. Nolan and David William Molloy. Their work appears in journals such as Journal of Quantitative Analysis in Sports, Health Services Research, Journal of Causal Inference, PLoS ONE and DOAJ (DOAJ: Directory of Open Access Journals).
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.