Daniel B. Neill
Impact in
- Health Informatics top 2%
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
Papers in
- Epidemiology 52
- Data-Driven Disease Surveillance 49
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- Anomaly Detection Techniques and Applications 25
- Bayesian Methods and Mixture Models 5
- Co-authors
- Andrew Moore (9 shared papers)Gregory F. Cooper (5 shared papers)Feng Chen (1 shared paper)Edward McFowland (6 shared papers)Skyler Speakman (4 shared papers)Maheshkumar Sabhnani (5 shared papers)Sufi M. Thomas (3 shared papers)Kenny Daniel (2 shared papers)
- Journals
- IEEE Intelligent Systems (4 papers)Statistics in Medicine (3 papers)Journal of Computational and Graphical Statistics (3 papers)American Journal of Epidemiology (3 papers)Journal of Theoretical Biology (2 papers)
- Partner nations
- United StatesBrazilUnited Kingdom
In The Last Decade
Daniel B. Neill
84 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 160
- Health Informatics 60
- Modeling and Simulation 129
- Artificial Intelligence 772
- Transportation 159
- Epidemiology 712
Countries citing papers authored by Daniel B. Neill
This map shows the geographic impact of Daniel B. 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 Daniel B. Neill with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel B. Neill more than expected).
Fields of papers citing papers by Daniel B. Neill
This network shows the impact of papers produced by Daniel B. 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 Daniel B. Neill. The network helps show where Daniel B. Neill may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel B. 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
Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 131 | |
| 2 | 2012 | 123 | |
| 3 | 2013 | 111 | |
| 4 | 2014 | 108 | |
| 5 | 2004 | 95 | |
| 6 | 2010 | 91 | |
| 7 | 2009 | 87 | |
| 8 | A Bayesian Spatial Scan Statistic | 2005 | 83 |
| 9 | 2005 | 82 | |
| 10 | 2008 | 63 | |
| 11 | 2009 | 59 | |
| 12 | 2009 | 56 | |
| 13 | 2010 | 51 | |
| 14 | 2018 | 50 | |
| 15 | 2009 | 48 | |
| 16 | Fast Generalized Subset Scan for Anomalous Pattern Detection | 2013 | 45 |
| 17 | 2010 | 41 | |
| 18 | 2015 | 40 | |
| 19 | Detection of spatial and spatio-temporal clusters | 2006 | 39 |
| 20 | Detecting Significant Multidimensional Spatial Clusters | 2004 | 37 |
About Daniel B. Neill
Daniel B. Neill is a scholar working on Epidemiology, Artificial Intelligence, Modeling and Simulation, Public Health, Environmental and Occupational Health and Transportation, having authored 93 papers that have together received 2.1k indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (49 papers), Anomaly Detection Techniques and Applications (25 papers), COVID-19 epidemiological studies (10 papers), Human Mobility and Location-Based Analysis (9 papers), Bayesian Methods and Mixture Models (5 papers), Zoonotic diseases and public health (4 papers), Opioid Use Disorder Treatment (4 papers) and Spatial and Panel Data Analysis (4 papers). The work is most often cited by research in Health Informatics (60 citations), Modeling and Simulation (129 citations), Artificial Intelligence (772 citations), Transportation (159 citations) and Epidemiology (712 citations). Daniel B. Neill has collaborated with scholars based in United States, Brazil and United Kingdom. Frequent co-authors include Andrew Moore, Gregory F. Cooper, Feng Chen, Edward McFowland, Skyler Speakman, Maheshkumar Sabhnani, Sufi M. Thomas, Kenny Daniel, Rebecca J. Leeman‐Neill and Kaustav Das. Their work appears in journals such as IEEE Intelligent Systems, Statistics in Medicine, Journal of Computational and Graphical Statistics, American Journal of Epidemiology and Journal of Theoretical Biology.
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.