Won Mok Shim
- Cognitive Neuroscience top 2%
- Experimental and Cognitive Psychology top 10%
- Social Psychology
- Computer Vision and Pattern Recognition top 10%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Yuhong JiangQing YuPatrick CavanaghGeorge A. AlvarezNancy KanwisherTal MakovskiSabin DangChristina Triantafyllou
- Topics
- Visual perception and processing mechanisms (26 papers)Neural dynamics and brain function (17 papers)Neural and Behavioral Psychology Studies (14 papers)
- Journals
- Proceedings of the National Academy of SciencesNature CommunicationsJournal of Neuroscience
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
Won Mok Shim
37 papers receiving 754 citations
Peers
Comparison fields: 5 of 69
- Cognitive Neuroscience 700
- Experimental and Cognitive Psychology 114
- Social Psychology 79
- Computer Vision and Pattern Recognition 64
- Radiology, Nuclear Medicine and Imaging 37
Countries citing papers authored by Won Mok Shim
This map shows the geographic impact of Won Mok Shim'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 Won Mok Shim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Won Mok Shim more than expected).
Fields of papers citing papers by Won Mok Shim
This network shows the impact of papers produced by Won Mok Shim. 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 Won Mok Shim. The network helps show where Won Mok Shim may publish in the future.
Co-authorship network of co-authors of Won Mok Shim
This figure shows the co-authorship network connecting the top 25 collaborators of Won Mok Shim. A scholar is included among the top collaborators of Won Mok Shim 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 Won Mok Shim. Won Mok Shim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 24 | |
| 5 | 6 | |
| 6 | 5 | |
| 7 | 9 | |
| 8 | 76 | |
| 9 | 39 | |
| 10 | 13 | |
| 11 | 6 | |
| 12 | 7 | |
| 13 | 24 | |
| 14 | 50 | |
| 15 | 34 | |
| 16 | 163 | |
| 17 | 15 | |
| 18 | 45 | |
| 19 | 22 | |
| 20 | 36 |
About Won Mok Shim
Won Mok Shim is a scholar working on Cognitive Neuroscience, Sensory Systems and Ophthalmology, having authored 39 papers that have together received 771 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (26 papers), Neural dynamics and brain function (17 papers) and Neural and Behavioral Psychology Studies (14 papers). The work is most often cited by research in Cognitive Neuroscience (700 citations), Experimental and Cognitive Psychology (114 citations) and Sensory Systems (32 citations). Won Mok Shim has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Yuhong Jiang, Qing Yu, Patrick Cavanagh, George A. Alvarez, Nancy Kanwisher, Tal Makovski, Sabin Dang, Christina Triantafyllou, Hans Op de Beeck and Mark Williams. 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.