Chang S. Nam
- Cognitive Neuroscience top 1%
- Human-Computer Interaction top 0.5%
- Cellular and Molecular Neuroscience top 5%
- Social Psychology top 2%
- Biomedical Engineering top 10%
- Co-authors
- Karen ChenTyler RoseYoungjoo KimYueqing LiSangwoo BahnYu ZhangGuoxu ZhouJing Jin
- Topics
- EEG and Brain-Computer Interfaces (50 papers)Neuroscience and Neural Engineering (24 papers)Neural and Behavioral Psychology Studies (19 papers)
- Partner nations
- United StatesSouth KoreaJapan
In The Last Decade
Chang S. Nam
105 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 142
- Cognitive Neuroscience 1.4k
- Human-Computer Interaction 501
- Cellular and Molecular Neuroscience 484
- Social Psychology 477
- Biomedical Engineering 311
Countries citing papers authored by Chang S. Nam
This map shows the geographic impact of Chang S. Nam'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 Chang S. Nam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang S. Nam more than expected).
Fields of papers citing papers by Chang S. Nam
This network shows the impact of papers produced by Chang S. Nam. 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 Chang S. Nam. The network helps show where Chang S. Nam may publish in the future.
Co-authorship network of co-authors of Chang S. Nam
This figure shows the co-authorship network connecting the top 25 collaborators of Chang S. Nam. A scholar is included among the top collaborators of Chang S. Nam 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 Chang S. Nam. Chang S. Nam 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 | 2 | |
| 4 | 2 | |
| 5 | 7 | |
| 6 | 13 | |
| 7 | 15 | |
| 8 | 3 | |
| 9 | 40 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 36 | |
| 13 | 29 | |
| 14 | Brain-Computer Interfaces Handbook: Technological and Theoretical Advances | 48 |
| 15 | Temporally Constrained Sparse Group Spatial Patterns for Motor Imagery BCIbreakdown → | 280 |
| 16 | 243 | |
| 17 | 91 | |
| 18 | 52 | |
| 19 | 9 | |
| 20 | Web-based instruction for high school students: exploration of individual and cultural learning styles | 2 |
About Chang S. Nam
Chang S. Nam is a scholar working on Human-Computer Interaction, Cognitive Neuroscience and Social Psychology, having authored 113 papers that have together received 2.5k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (50 papers), Neuroscience and Neural Engineering (24 papers) and Neural and Behavioral Psychology Studies (19 papers). The work is most often cited by research in Human-Computer Interaction (501 citations), Cognitive Neuroscience (1.4k citations) and Cellular and Molecular Neuroscience (484 citations). Chang S. Nam has collaborated with scholars based in United States, South Korea and Japan. Frequent co-authors include Karen Chen, Tyler Rose, Youngjoo Kim, Yueqing Li, Sangwoo Bahn, Yu Zhang, Guoxu Zhou, Jing Jin, Xingyu Wang and Andrzej Cichocki. Their work appears in journals such as PLoS ONE, Computers in Human Behavior and Expert Systems with Applications.
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.