David D. Ellison
Impact in
- Software top 10%
- Software Reliability and Analysis Research
- Environmental Engineering top 10%
- Soil Geostatistics and Mapping
- Soil Moisture and Remote Sensing
Papers in
-
- Explainable Artificial Intelligence (XAI) 7
- Data Stream Mining Techniques 5
- Machine Learning and Data Classification 4
- Adversarial Robustness in Machine Learning 3
-
- Artificial Intelligence in Healthcare and Education 3
- Co-authors
- Lee D. Baker (2 shared papers)Andre Levchenko (7 shared papers)David A. McClellan (1 shared paper)Pat Dugard (1 shared paper)Kshitiz Gupta (4 shared papers)Deok‐Ho Kim (3 shared papers)Christopher L. Smith (2 shared papers)Arnab Kundu (1 shared paper)
- Journals
- Geoderma (2 papers)Proceedings of the National Academy of Sciences (2 papers)Integrative Biology (1 paper)Information and Software Technology (1 paper)Expert Systems with Applications (1 paper)
- Partner nations
- United StatesSpainChina
In The Last Decade
David D. Ellison
20 papers receiving 554 citations
Peers
Comparison fields: 5 of 112
- Software 50
- Environmental Engineering 84
- Biomedical Engineering 208
- Cell Biology 75
- Soil Science 40
Countries citing papers authored by David D. Ellison
This map shows the geographic impact of David D. Ellison'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 David D. Ellison with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David D. Ellison more than expected).
Fields of papers citing papers by David D. Ellison
This network shows the impact of papers produced by David D. Ellison. 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 David D. Ellison. The network helps show where David D. Ellison may publish in the future.
Co-authors
The 25 scholars most cited alongside David D. Ellison, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 119 | |
| 2 | 2016 | 118 | |
| 3 | 2008 | 89 | |
| 4 | 1997 | 61 | |
| 5 | 2010 | 40 | |
| 6 | 2009 | 38 | |
| 7 | 2008 | 37 | |
| 8 | 2019 | 25 | |
| 9 | 2015 | 8 | |
| 10 | 2022 | 7 | |
| 11 | 2022 | 6 | |
| 12 | 2022 | 6 | |
| 13 | 2021 | 5 | |
| 14 | 2021 | 5 | |
| 15 | 2019 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2010 | 3 | |
| 18 | 2023 | 3 | |
| 19 | 2023 | 2 | |
| 20 | 2022 | 2 |
About David D. Ellison
David D. Ellison is a scholar working on Artificial Intelligence, Health Informatics, Cell Biology, Biomedical Engineering and Information Systems, having authored 22 papers that have together received 583 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (7 papers), Data Stream Mining Techniques (5 papers), 3D Printing in Biomedical Research (5 papers), Machine Learning and Data Classification (4 papers), Microfluidic and Bio-sensing Technologies (3 papers), Cellular Mechanics and Interactions (3 papers), Adversarial Robustness in Machine Learning (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). The work is most often cited by research in Software (50 citations), Environmental Engineering (84 citations), Biomedical Engineering (208 citations), Cell Biology (75 citations) and Soil Science (40 citations). David D. Ellison has collaborated with scholars based in United States, Spain and China. Frequent co-authors include Lee D. Baker, Andre Levchenko, David A. McClellan, Pat Dugard, Kshitiz Gupta, Deok‐Ho Kim, Christopher L. Smith, Arnab Kundu, Kahp-Yang Suh and Andrew J. Ewald. Their work appears in journals such as Geoderma, Proceedings of the National Academy of Sciences, Integrative Biology, Information and Software Technology and Expert Systems with Applications.
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.