Matthew R. Masters
- Biomedical Engineering
- Cognitive Neuroscience top 10%
- Molecular Biology
- Cellular and Molecular Neuroscience
- Computational Theory and Mathematics top 10%
- Co-authors
- Nitish V. ThakorMarkus A. LillAmr H. MahmoudRahul R. KalikiJoseph BetthauserLuke E. OsbornYang YingChristopher L. Hunt
- Topics
- Protein Structure and Dynamics (5 papers)Neuroscience and Neural Engineering (5 papers)Machine Learning in Materials Science (4 papers)
- Journals
- Nature CommunicationsIEEE Transactions on Biomedical EngineeringJournal of Chemical Information and Modeling
- Partner nations
- United StatesSwitzerlandBrazil
In The Last Decade
Matthew R. Masters
13 papers receiving 272 citations
Peers
Comparison fields: 5 of 70
- Biomedical Engineering 123
- Cognitive Neuroscience 104
- Molecular Biology 87
- Cellular and Molecular Neuroscience 85
- Computational Theory and Mathematics 61
Countries citing papers authored by Matthew R. Masters
This map shows the geographic impact of Matthew R. Masters'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. Masters 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. Masters more than expected).
Fields of papers citing papers by Matthew R. Masters
This network shows the impact of papers produced by Matthew R. Masters. 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. Masters. The network helps show where Matthew R. Masters may publish in the future.
Co-authorship network of co-authors of Matthew R. Masters
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew R. Masters. A scholar is included among the top collaborators of Matthew R. Masters based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthew R. Masters. Matthew R. Masters is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 32 | |
| 4 | 1 | |
| 5 | 8 | |
| 6 | 46 | |
| 7 | 4 | |
| 8 | 16 | |
| 9 | 26 | |
| 10 | 80 | |
| 11 | 37 | |
| 12 | 5 | |
| 13 | 7 | |
| 14 | 7 |
About Matthew R. Masters
Matthew R. Masters is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Computational Theory and Mathematics, having authored 14 papers that have together received 276 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Neuroscience and Neural Engineering (5 papers) and Machine Learning in Materials Science (4 papers). The work is most often cited by research in Cognitive Neuroscience (104 citations), Cellular and Molecular Neuroscience (85 citations) and Human-Computer Interaction (22 citations). Matthew R. Masters has collaborated with scholars based in United States, Switzerland and Brazil. Frequent co-authors include Nitish V. Thakor, Markus A. Lill, Amr H. Mahmoud, Rahul R. Kaliki, Joseph Betthauser, Luke E. Osborn, Yang Ying, Christopher L. Hunt, Alcimar Barbosa Soares and Ying Yang. Their work appears in journals such as Nature Communications, IEEE Transactions on Biomedical Engineering and Journal of Chemical Information and Modeling.
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.