Eva L. Dyer
Impact in
- Structural Biology top 5%
- Advanced Electron Microscopy Techniques and Applications
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
-
- Neural dynamics and brain function 11
- Functional Brain Connectivity Studies 4
- EEG and Brain-Computer Interfaces 3
- Co-authors
- Richard G. Baraniuk (5 shared papers)Mary-Elizabeth Hamstrom (1 shared paper)Aswin C. Sankaranarayanan (1 shared paper)Narayanan Kasthuri (4 shared papers)Doğa Gürsoy (5 shared papers)Vincent De Andrade (3 shared papers)Konrad P. Körding (6 shared papers)Lee E. Miller (2 shared papers)
- Journals
- Nature Biomedical Engineering (2 papers)eNeuro (1 paper)Scientific Reports (1 paper)Cell Reports (1 paper)Journal of Neuroscience (1 paper)
- Partner nations
- United StatesCanadaPhilippines
In The Last Decade
Eva L. Dyer
32 papers receiving 518 citations
Peers
Comparison fields: 5 of 93
- Structural Biology 42
- Biophysics 50
- Cognitive Neuroscience 141
- Radiation 46
- Geometry and Topology 43
Countries citing papers authored by Eva L. Dyer
This map shows the geographic impact of Eva L. Dyer'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 Eva L. Dyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eva L. Dyer more than expected).
Fields of papers citing papers by Eva L. Dyer
This network shows the impact of papers produced by Eva L. Dyer. 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 Eva L. Dyer. The network helps show where Eva L. Dyer may publish in the future.
Co-authors
The 25 scholars most cited alongside Eva L. Dyer, 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 39 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 94 | |
| 2 | 2018 | 68 | |
| 3 | 1958 | 68 | |
| 4 | 2018 | 66 | |
| 5 | 2017 | 62 | |
| 6 | 2023 | 47 | |
| 7 | 2017 | 31 | |
| 8 | 2010 | 18 | |
| 9 | 2020 | 11 | |
| 10 | 2022 | 9 | |
| 11 | 2020 | 9 | |
| 12 | 2023 | 8 | |
| 13 | 2024 | 7 | |
| 14 | 2018 | 7 | |
| 15 | 2013 | 7 | |
| 16 | 2013 | 7 | |
| 17 | 2019 | 7 | |
| 18 | 2019 | 6 | |
| 19 | 2018 | 6 | |
| 20 | 2020 | 4 |
About Eva L. Dyer
Eva L. Dyer is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Biophysics, having authored 39 papers that have together received 563 indexed citations. Recurring topics across this work include Neural dynamics and brain function (11 papers), Cell Image Analysis Techniques (6 papers), Sparse and Compressive Sensing Techniques (4 papers), Functional Brain Connectivity Studies (4 papers), Advanced MRI Techniques and Applications (4 papers), Medical Image Segmentation Techniques (3 papers), Neuroscience and Neural Engineering (3 papers) and EEG and Brain-Computer Interfaces (3 papers). The work is most often cited by research in Structural Biology (42 citations), Biophysics (50 citations), Cognitive Neuroscience (141 citations), Radiation (46 citations) and Geometry and Topology (43 citations). Eva L. Dyer has collaborated with scholars based in United States, Canada and Philippines. Frequent co-authors include Richard G. Baraniuk, Mary-Elizabeth Hamstrom, Aswin C. Sankaranarayanan, Narayanan Kasthuri, Doğa Gürsoy, Vincent De Andrade, Konrad P. Körding, Lee E. Miller, Hugo L. Fernandes and Francesco De Carlo. Their work appears in journals such as Nature Biomedical Engineering, eNeuro, Scientific Reports, Cell Reports and Journal of Neuroscience.
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.