Facai Wu
Impact in
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Semiconductor materials and devices
Papers in
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- Advanced Memory and Neural Computing 18
- Ferroelectric and Negative Capacitance Devices 8
- Semiconductor materials and devices 3
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- Neuroscience and Neural Engineering 8
- Photoreceptor and optogenetics research 8
- Co-authors
- Qi Liu (9 shared papers)Xumeng Zhang (7 shared papers)Xiaolong Zhao (6 shared papers)Quantan Wu (5 shared papers)Ming Liu (4 shared papers)Rongrong Cao (4 shared papers)Hangbing Lv (4 shared papers)Tseung‐Yuen Tseng (5 shared papers)
In The Last Decade
Facai Wu
18 papers receiving 816 citations
Peers
Comparison fields: 5 of 35
- Cellular and Molecular Neuroscience 406
- Electrical and Electronic Engineering 793
- Polymers and Plastics 173
- Cognitive Neuroscience 118
- Artificial Intelligence 94
Countries citing papers authored by Facai Wu
This map shows the geographic impact of Facai 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 Facai Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Facai Wu more than expected).
Fields of papers citing papers by Facai Wu
This network shows the impact of papers produced by Facai 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 Facai Wu. The network helps show where Facai Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Facai 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
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 162 | |
| 2 | 2021 | 131 | |
| 3 | 2020 | 122 | |
| 4 | 2018 | 104 | |
| 5 | 2019 | 60 | |
| 6 | 2017 | 36 | |
| 7 | 2019 | 36 | |
| 8 | 2018 | 32 | |
| 9 | 2021 | 30 | |
| 10 | 2023 | 22 | |
| 11 | 2018 | 21 | |
| 12 | 2017 | 17 | |
| 13 | 2024 | 16 | |
| 14 | 2022 | 15 | |
| 15 | 2022 | 14 | |
| 16 | 2017 | 10 | |
| 17 | 2018 | 5 | |
| 18 | 2023 | 1 |
About Facai Wu
Facai Wu is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Polymers and Plastics, Cognitive Neuroscience and Artificial Intelligence, having authored 18 papers that have together received 834 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (18 papers), Ferroelectric and Negative Capacitance Devices (8 papers), Neuroscience and Neural Engineering (8 papers), Photoreceptor and optogenetics research (8 papers), Transition Metal Oxide Nanomaterials (3 papers), Semiconductor materials and devices (3 papers), Neural Networks and Reservoir Computing (2 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (406 citations), Electrical and Electronic Engineering (793 citations), Polymers and Plastics (173 citations), Cognitive Neuroscience (118 citations) and Artificial Intelligence (94 citations). Facai Wu has collaborated with scholars based in China, Taiwan and Singapore. Frequent co-authors include Qi Liu, Xumeng Zhang, Xiaolong Zhao, Quantan Wu, Ming Liu, Rongrong Cao, Hangbing Lv, Tseung‐Yuen Tseng, Shibing Long and Tuo Shi. Their work appears in journals such as IEEE Transactions on Electron Devices, Applied Physics Letters, IEEE Electron Device Letters, Nanoscale Research Letters and Advanced Electronic Materials.
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.