Michael L. Mack
- Cognitive Neuroscience top 1%
- Computer Vision and Pattern Recognition top 2%
- Experimental and Cognitive Psychology top 5%
- Developmental and Educational Psychology top 5%
- Social Psychology top 5%
- Co-authors
- Thomas J. PalmeriAlison R. PrestonBradley C. LoveL. GauthierJohn M. HendersonMonica S. CastelhanoJennifer J. RichlerBowen Du
- Topics
- Face Recognition and Perception (18 papers)Child and Animal Learning Development (12 papers)Memory and Neural Mechanisms (10 papers)
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsJournal of Neuroscience
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
Michael L. Mack
40 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 130
- Cognitive Neuroscience 1.3k
- Computer Vision and Pattern Recognition 440
- Experimental and Cognitive Psychology 349
- Developmental and Educational Psychology 237
- Social Psychology 213
Countries citing papers authored by Michael L. Mack
This map shows the geographic impact of Michael L. Mack'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 Michael L. Mack with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael L. Mack more than expected).
Fields of papers citing papers by Michael L. Mack
This network shows the impact of papers produced by Michael L. Mack. 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 Michael L. Mack. The network helps show where Michael L. Mack may publish in the future.
Co-authorship network of co-authors of Michael L. Mack
This figure shows the co-authorship network connecting the top 25 collaborators of Michael L. Mack. A scholar is included among the top collaborators of Michael L. Mack 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 Michael L. Mack. Michael L. Mack 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 | 0 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 2 | |
| 9 | 16 | |
| 10 | 14 | |
| 11 | 105 | |
| 12 | 2 | |
| 13 | 126 | |
| 14 | 110 | |
| 15 | 2 | |
| 16 | 38 | |
| 17 | 137 | |
| 18 | 23 | |
| 19 | 28 | |
| 20 | Identifying the Perceptual Dimensions of Visual Complexity of Scenes | 136 |
About Michael L. Mack
Michael L. Mack is a scholar working on Cognitive Neuroscience, Developmental and Educational Psychology and Experimental and Cognitive Psychology, having authored 44 papers that have together received 1.7k indexed citations. Recurring topics across this work include Face Recognition and Perception (18 papers), Child and Animal Learning Development (12 papers) and Memory and Neural Mechanisms (10 papers). The work is most often cited by research in Cognitive Neuroscience (1.3k citations), Experimental and Cognitive Psychology (349 citations) and Human-Computer Interaction (133 citations). Michael L. Mack has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Thomas J. Palmeri, Alison R. Preston, Bradley C. Love, L. Gauthier, John M. Henderson, Monica S. Castelhano, Jennifer J. Richler, Bowen Du, Jeffrey A. Siegel and Javid Sadr. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications 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.