Matthew R. DeWitt
Impact in
- Biotechnology top 1%
- Microbial Inactivation Methods
- Modeling and Simulation top 5%
- Mathematical Biology Tumor Growth
Papers in
-
- Microbial Inactivation Methods 14
-
- Microfluidic and Bio-sensing Technologies 6
- Ultrasound and Hyperthermia Applications 4
- Nanoplatforms for cancer theranostics 3
- Co-authors
- Michael B. Sano (9 shared papers)Rafael V. Davalos (9 shared papers)Marissa Nichole Rylander (6 shared papers)Dieter Saur (2 shared papers)Christopher B. Arena (3 shared papers)Allison M. Pekkanen (2 shared papers)Eduardo L. Latouche (6 shared papers)Lei Xing (2 shared papers)
- Journals
- HPB (3 papers)IEEE Transactions on Biomedical Engineering (3 papers)Frontiers in Veterinary Science (2 papers)Bioelectrochemistry (1 paper)Annals of Biomedical Engineering (1 paper)
- Partner nations
- United StatesGermanyBrazil
In The Last Decade
Matthew R. DeWitt
21 papers receiving 702 citations
Peers
Comparison fields: 5 of 81
- Biotechnology 427
- Modeling and Simulation 58
- Physiology 54
- Biomedical Engineering 362
- Radiology, Nuclear Medicine and Imaging 89
Countries citing papers authored by Matthew R. DeWitt
This map shows the geographic impact of Matthew R. DeWitt'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 Matthew R. DeWitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew R. DeWitt more than expected).
Fields of papers citing papers by Matthew R. DeWitt
This network shows the impact of papers produced by Matthew R. DeWitt. 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 Matthew R. DeWitt. The network helps show where Matthew R. DeWitt may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew R. DeWitt, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 110 | |
| 2 | 2015 | 110 | |
| 3 | 2015 | 71 | |
| 4 | 2014 | 61 | |
| 5 | 2016 | 58 | |
| 6 | 2018 | 54 | |
| 7 | 2017 | 47 | |
| 8 | 2018 | 36 | |
| 9 | 2017 | 30 | |
| 10 | 2018 | 28 | |
| 11 | 2013 | 22 | |
| 12 | 2019 | 20 | |
| 13 | 2013 | 19 | |
| 14 | 2019 | 13 | |
| 15 | 2014 | 7 | |
| 16 | 2018 | 7 | |
| 17 | 2024 | 7 | |
| 18 | 2020 | 4 | |
| 19 | 2025 | 2 | |
| 20 | 2016 | 1 |
About Matthew R. DeWitt
Matthew R. DeWitt is a scholar working on Biotechnology, Biomedical Engineering, Physiology, Immunology and Biomaterials, having authored 23 papers that have together received 708 indexed citations. Recurring topics across this work include Microbial Inactivation Methods (14 papers), Microfluidic and Bio-sensing Technologies (6 papers), Magnetic and Electromagnetic Effects (4 papers), Ultrasound and Hyperthermia Applications (4 papers), Toxin Mechanisms and Immunotoxins (3 papers), Nanoplatforms for cancer theranostics (3 papers), Nanoparticle-Based Drug Delivery (2 papers) and Cancer Cells and Metastasis (2 papers). The work is most often cited by research in Biotechnology (427 citations), Modeling and Simulation (58 citations), Physiology (54 citations), Biomedical Engineering (362 citations) and Radiology, Nuclear Medicine and Imaging (89 citations). Matthew R. DeWitt has collaborated with scholars based in United States, Germany and Brazil. Frequent co-authors include Michael B. Sano, Rafael V. Davalos, Marissa Nichole Rylander, Dieter Saur, Christopher B. Arena, Allison M. Pekkanen, Eduardo L. Latouche, Lei Xing, John L. Robertson and Jacob H. Swet. Their work appears in journals such as HPB, IEEE Transactions on Biomedical Engineering, Frontiers in Veterinary Science, Bioelectrochemistry and Annals of Biomedical Engineering.
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.