Stephen I. Ryu
- Cognitive Neuroscience top 0.2%
- EEG and Brain-Computer Interfaces 30
- Neural dynamics and brain function 26
- Motor Control and Adaptation 11
- Cellular and Molecular Neuroscience top 0.5%
- Neuroscience and Neural Engineering 19
- Computational Mathematics top 2%
- Biochemistry top 0.5%
- Lipid metabolism and biosynthesis 11
- Plant Science top 2%
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- Plant biochemistry and biosynthesis 12
- Photosynthetic Processes and Mechanisms 9
- Plant Reproductive Biology 8
- Co-authors
- Krishna V. ShenoyMatthew T. KaufmanMark M. ChurchlandJohn P. CunninghamXuemin WangPaul NuyujukianByron M. YuJustin Foster
- Partner nations
- United StatesSouth KoreaUnited Kingdom
In The Last Decade
Stephen I. Ryu
92 papers receiving 7.4k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Cognitive Neuroscience 4.5k
- Cellular and Molecular Neuroscience 2.1k
- Computational Mathematics 46
- Biochemistry 523
- Plant Science 1.2k
Countries citing papers authored by Stephen I. Ryu
This map shows the geographic impact of Stephen I. Ryu'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 Stephen I. Ryu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen I. Ryu more than expected).
Fields of papers citing papers by Stephen I. Ryu
This network shows the impact of papers produced by Stephen I. Ryu. 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 Stephen I. Ryu. The network helps show where Stephen I. Ryu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Stephen I. Ryu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2022 | 44 | |
| 3 | 2021 | 52 | |
| 4 | 2018 | 22 | |
| 5 | 2018 | 6 | |
| 6 | 2016 | 133 | |
| 7 | 2016 | 32 | |
| 8 | 2016 | 37 | |
| 9 | 2015 | 61 | |
| 10 | 2015 | 100 | |
| 11 | Cortical activity in the null space: permitting preparation without movementbreakdown → | 2014 | 451 |
| 12 | 2012 | 17 | |
| 13 | 2012 | 70 | |
| 14 | Dynamical segmentation of single trials from population neural data | 2011 | 34 |
| 15 | 2010 | 317 | |
| 16 | 2008 | 133 | |
| 17 | 2005 | 41 | |
| 18 | Extracting Dynamical Structure Embedded in Neural Activity | 2005 | 48 |
| 19 | 2003 | 102 | |
| 20 | 2001 | 246 |
About Stephen I. Ryu
Stephen I. Ryu is a scholar working on Cognitive Neuroscience, Computational Mathematics and Biochemistry, having authored 92 papers that have together received 7.6k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (30 papers), Neural dynamics and brain function (26 papers), Neuroscience and Neural Engineering (19 papers), Plant biochemistry and biosynthesis (12 papers), Motor Control and Adaptation (11 papers), Lipid metabolism and biosynthesis (11 papers), Photosynthetic Processes and Mechanisms (9 papers) and Plant Reproductive Biology (8 papers). The work is most often cited by research in Cognitive Neuroscience (4.5k citations), Cellular and Molecular Neuroscience (2.1k citations) and Computational Mathematics (46 citations). Stephen I. Ryu has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Krishna V. Shenoy, Matthew T. Kaufman, Mark M. Churchland, John P. Cunningham, Xuemin Wang, Paul Nuyujukian, Byron M. Yu, Justin Foster, Jonathan C. Kao and Gopal Santhanam. Their work appears in journals such as Neuron, PLANT PHYSIOLOGY, Nature Neuroscience, Nature and Industrial Crops and Products.
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.