Si Wu
Impact in
- Cognitive Neuroscience top 2%
- Neural dynamics and brain function
- Visual perception and processing mechanisms
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- Neuroscience and Neuropharmacology Research
- Neuroscience and Neural Engineering
Papers in
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- Neural dynamics and brain function 61
- Visual perception and processing mechanisms 17
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- Neural Networks and Applications 23
- Co-authors
- Шун-ичи Амари (10 shared papers)Hiroyuki Nakahara (5 shared papers)Malte J. Rasch (7 shared papers)Kang Lee (9 shared papers)K. Y. Michael Wong (14 shared papers)Luo Hong (5 shared papers)Misha Tsodyks (2 shared papers)Genyue Fu (5 shared papers)
- Journals
- Neural Computation (10 papers)Neural Networks (6 papers)eLife (4 papers)Nature Communications (3 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Si Wu
79 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 119
- Cognitive Neuroscience 999
- Cellular and Molecular Neuroscience 377
- Statistical and Nonlinear Physics 186
- Sensory Systems 57
- Experimental and Cognitive Psychology 122
Countries citing papers authored by Si Wu
This map shows the geographic impact of Si Wu'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 Si Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Si Wu more than expected).
Fields of papers citing papers by Si Wu
This network shows the impact of papers produced by Si Wu. 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 Si Wu. The network helps show where Si Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Si Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 178 | |
| 2 | 2002 | 107 | |
| 3 | 2014 | 105 | |
| 4 | 2003 | 102 | |
| 5 | 2007 | 74 | |
| 6 | 2001 | 73 | |
| 7 | 2013 | 46 | |
| 8 | 2005 | 44 | |
| 9 | 2009 | 44 | |
| 10 | 2016 | 39 | |
| 11 | 2013 | 35 | |
| 12 | 2018 | 35 | |
| 13 | 2012 | 34 | |
| 14 | 2016 | 34 | |
| 15 | 2015 | 29 | |
| 16 | 2015 | 27 | |
| 17 | 2019 | 26 | |
| 18 | 2018 | 25 | |
| 19 | 2003 | 22 | |
| 20 | 2016 | 22 |
About Si Wu
Si Wu is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Statistical and Nonlinear Physics, having authored 88 papers that have together received 1.5k indexed citations. Recurring topics across this work include Neural dynamics and brain function (61 papers), Neural Networks and Applications (23 papers), Advanced Memory and Neural Computing (22 papers), Visual perception and processing mechanisms (17 papers), Neuroscience and Neuropharmacology Research (14 papers), stochastic dynamics and bifurcation (9 papers), Photoreceptor and optogenetics research (7 papers) and Multisensory perception and integration (6 papers). The work is most often cited by research in Cognitive Neuroscience (999 citations), Cellular and Molecular Neuroscience (377 citations), Statistical and Nonlinear Physics (186 citations), Sensory Systems (57 citations) and Experimental and Cognitive Psychology (122 citations). Si Wu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Шун-ичи Амари, Hiroyuki Nakahara, Malte J. Rasch, Kang Lee, K. Y. Michael Wong, Luo Hong, Misha Tsodyks, Genyue Fu, Yutaka Sakai and Kosuke Hamaguchi. Their work appears in journals such as Neural Computation, Neural Networks, eLife, Nature Communications and Scientific Reports.
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.