David A. Haggerty
Impact in
- Toxicology top 5%
- Forensic Toxicology and Drug Analysis
Papers in
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- Soft Robotics and Applications 6
-
- Modular Robots and Swarm Intelligence 4
- Co-authors
- Elliot W. Hawkes (8 shared papers)Jolene Okaneku (1 shared paper)Michael I. Greenberg (1 shared paper)David Vearrier (1 shared paper)Nicholas D. Naclerio (4 shared papers)Laura H. Blumenschein (1 shared paper)Allison M. Okamura (1 shared paper)Gregory B. Young (1 shared paper)
- Journals
- IEEE Robotics and Automation Letters (2 papers)Gastroenterology (1 paper)Science Translational Medicine (1 paper)Journal of Emergency Medicine (1 paper)Journal of Medical Toxicology (1 paper)
- Partner nations
- United StatesCroatiaJapan
In The Last Decade
David A. Haggerty
14 papers receiving 588 citations
Peers
Comparison fields: 5 of 122
- Toxicology 44
- Biochemistry 33
- Condensed Matter Physics 48
- Biomedical Engineering 167
- Mechanical Engineering 116
Countries citing papers authored by David A. Haggerty
This map shows the geographic impact of David A. Haggerty'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 A. Haggerty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David A. Haggerty more than expected).
Fields of papers citing papers by David A. Haggerty
This network shows the impact of papers produced by David A. Haggerty. 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 A. Haggerty. The network helps show where David A. Haggerty may publish in the future.
Co-authors
The 25 scholars most cited alongside David A. Haggerty, 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 | 1999 | 191 | |
| 2 | 2012 | 137 | |
| 3 | 2020 | 69 | |
| 4 | 2023 | 64 | |
| 5 | 2019 | 33 | |
| 6 | 2021 | 23 | |
| 7 | 2014 | 21 | |
| 8 | 2002 | 17 | |
| 9 | 2019 | 13 | |
| 10 | 2020 | 12 | |
| 11 | 2005 | 10 | |
| 12 | 2023 | 6 | |
| 13 | 2020 | 2 | |
| 14 | 2003 | 1 | |
| 15 | 2025 | 0 |
About David A. Haggerty
David A. Haggerty is a scholar working on Biomedical Engineering, Mechanical Engineering, Molecular Biology, Condensed Matter Physics and Cell Biology, having authored 15 papers that have together received 599 indexed citations. Recurring topics across this work include Soft Robotics and Applications (6 papers), Modular Robots and Swarm Intelligence (4 papers), Micro and Nano Robotics (3 papers), Lattice Boltzmann Simulation Studies (2 papers), Aldose Reductase and Taurine (2 papers), Model Reduction and Neural Networks (2 papers), Airway Management and Intubation Techniques (1 paper) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Toxicology (44 citations), Biochemistry (33 citations), Condensed Matter Physics (48 citations), Biomedical Engineering (167 citations) and Mechanical Engineering (116 citations). David A. Haggerty has collaborated with scholars based in United States, Croatia and Japan. Frequent co-authors include Elliot W. Hawkes, Jolene Okaneku, Michael I. Greenberg, David Vearrier, Nicholas D. Naclerio, Laura H. Blumenschein, Allison M. Okamura, Gregory B. Young, Eric C. Lai and Marek K. Sliwinski. Their work appears in journals such as IEEE Robotics and Automation Letters, Gastroenterology, Science Translational Medicine, Journal of Emergency Medicine and Journal of Medical Toxicology.
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.