David Yu
- Cognitive Neuroscience top 5%
- Face Recognition and Perception 2
- Functional Brain Connectivity Studies 2
- Neural dynamics and brain function 1
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- Advanced Neuroimaging Techniques and Applications 2
- Advanced MRI Techniques and Applications 2
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- Photoreceptor and optogenetics research 1
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- Natural Language Processing Techniques 2
- Neural Networks and Applications 1
- Co-authors
- David A. LeopoldFrank Q. YeColin ReveleyAfonso C. SilvaAnil K. SethRichard C. SaundersCarlo PierpaoliJanita Turchi
- Journals
- Proceedings of the National Academy of Sciences (2 papers)Science Advances (1 paper)Neuron (1 paper)
- Partner nations
- United StatesAustraliaUnited Kingdom
In The Last Decade
David Yu
9 papers receiving 532 citations
Hit Papers
Peers
Comparison fields: 5 of 58
- Cognitive Neuroscience 406
- Radiology, Nuclear Medicine and Imaging 324
- Computational Mathematics 4
- Neurology 37
- Cellular and Molecular Neuroscience 60
Countries citing papers authored by David Yu
This map shows the geographic impact of David Yu'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 David Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Yu more than expected).
Fields of papers citing papers by David Yu
This network shows the impact of papers produced by David Yu. 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 David Yu. The network helps show where David Yu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David Yu, 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 | 2022 | 8 | |
| 2 | 2022 | 10 | |
| 3 | 2021 | 8 | |
| 4 | 2018 | 150 | |
| 5 | Superficial white matter fiber systems impede detection of long-range cortical connections in diffusion MR tractographybreakdown → | 2015 | 294 |
| 6 | 2009 | 61 | |
| 7 | Nathu IR System at NTCIR-II. | 2001 | 2 |
| 8 | 統計式片語翻譯模型 (Statistical Translation Model for Phrases) [In Chinese] | 2001 | 2 |
| 9 | Statistical Translation Model for Phrases. | 2001 | 3 |
About David Yu
David Yu is a scholar working on Cognitive Neuroscience, Sensory Systems, Complementary and alternative medicine, Neurology and Cellular and Molecular Neuroscience, having authored 9 papers that have together received 538 indexed citations. Recurring topics across this work include Face Recognition and Perception (2 papers), Functional Brain Connectivity Studies (2 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Natural Language Processing Techniques (2 papers), Advanced MRI Techniques and Applications (2 papers), Neural dynamics and brain function (1 paper), Photoreceptor and optogenetics research (1 paper) and Neural Networks and Applications (1 paper). The work is most often cited by research in Cognitive Neuroscience (406 citations), Radiology, Nuclear Medicine and Imaging (324 citations), Computational Mathematics (4 citations), Neurology (37 citations) and Cellular and Molecular Neuroscience (60 citations). David Yu has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include David A. Leopold, Frank Q. Ye, Colin Reveley, Afonso C. Silva, Anil K. Seth, Richard C. Saunders, Carlo Pierpaoli, Janita Turchi, Ilya E. Monosov and Catie Chang. Their work appears in journals such as Proceedings of the National Academy of Sciences, Science Advances, Neuron, Journal of Neuroscience and NeuroImage.
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.