Mary J. Bravo
- Cognitive Neuroscience top 2%
- Computer Vision and Pattern Recognition top 5%
- Experimental and Cognitive Psychology top 10%
- Social Psychology top 10%
- Human-Computer Interaction top 5%
- Co-authors
- Hany FaridKen NakayamaRandolph BlakeSharon D. MorrisonSuzanne P. McKeeGordon E. LeggeScott WatamaniukD TAYLOR
- Topics
- Visual perception and processing mechanisms (18 papers)Neural and Behavioral Psychology Studies (9 papers)Face Recognition and Perception (8 papers)
- Cited by
- Cognitive NeuroscienceComputer Vision and Pattern RecognitionExperimental and Cognitive Psychology
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
Mary J. Bravo
27 papers receiving 924 citations
Peers
Comparison fields: 5 of 86
- Cognitive Neuroscience 744
- Computer Vision and Pattern Recognition 348
- Experimental and Cognitive Psychology 146
- Social Psychology 121
- Human-Computer Interaction 59
Countries citing papers authored by Mary J. Bravo
This map shows the geographic impact of Mary J. Bravo'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 Mary J. Bravo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mary J. Bravo more than expected).
Fields of papers citing papers by Mary J. Bravo
This network shows the impact of papers produced by Mary J. Bravo. 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 Mary J. Bravo. The network helps show where Mary J. Bravo may publish in the future.
Co-authorship network of co-authors of Mary J. Bravo
This figure shows the co-authorship network connecting the top 25 collaborators of Mary J. Bravo. A scholar is included among the top collaborators of Mary J. Bravo 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 Mary J. Bravo. Mary J. Bravo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 8 | |
| 3 | 3 | |
| 4 | 8 | |
| 5 | 1 | |
| 6 | 33 | |
| 7 | 56 | |
| 8 | 66 | |
| 9 | 49 | |
| 10 | 23 | |
| 11 | 48 | |
| 12 | 13 | |
| 13 | 10 | |
| 14 | 27 | |
| 15 | 27 | |
| 16 | 36 | |
| 17 | 5 | |
| 18 | 320 | |
| 19 | 62 | |
| 20 | 73 |
About Mary J. Bravo
Mary J. Bravo is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology, having authored 27 papers that have together received 964 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (18 papers), Neural and Behavioral Psychology Studies (9 papers) and Face Recognition and Perception (8 papers). The work is most often cited by research in Cognitive Neuroscience (744 citations), Computer Vision and Pattern Recognition (348 citations) and Experimental and Cognitive Psychology (146 citations). Mary J. Bravo has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include Hany Farid, Ken Nakayama, Randolph Blake, Sharon D. Morrison, Suzanne P. McKee, Gordon E. Legge, Scott Watamaniuk, D TAYLOR, Harvey S. Smallman and Benedetto Piccoli. Their work appears in journals such as Vision Research, Memory & Cognition and Journal of Vision.
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.