Can Wu
Impact in
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- Thin-Film Transistor Technologies
- Organic Light-Emitting Diodes Research
- Organic Electronics and Photovoltaics
- Semiconductor materials and devices
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- Conducting polymers and applications
Papers in
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- Thin-Film Transistor Technologies 8
- Energy Harvesting in Wireless Networks 2
- CCD and CMOS Imaging Sensors 2
- Radio Frequency Integrated Circuit Design 2
- Advanced Memory and Neural Computing 2
- Co-authors
- S. WagnerG. GuJ. C. SturmM. LuStephen R. ForrestJames C. SturmNaveen VermaWarren Rieutort‐Louis
- Journals
- IEEE Journal of Solid-State Circuits (2 papers)IEEE Electron Device Letters (1 paper)Journal of Materials Chemistry C (1 paper)Integrated ferroelectrics (1 paper)Nature Electronics (1 paper)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Can Wu
20 papers receiving 277 citations
Peers
Comparison fields: 5 of 32
- Electrical and Electronic Engineering 222
- Polymers and Plastics 42
- Biomedical Engineering 105
- Cellular and Molecular Neuroscience 25
- Cognitive Neuroscience 21
Countries citing papers authored by Can Wu
This map shows the geographic impact of Can 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 Can Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Can Wu more than expected).
Fields of papers citing papers by Can Wu
This network shows the impact of papers produced by Can 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 Can Wu. The network helps show where Can Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Can 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 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 4 | |
| 5 | 2024 | 11 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 6 | |
| 8 | 2023 | 2 | |
| 9 | 2022 | 1 | |
| 10 | 2022 | 3 | |
| 11 | 2021 | 18 | |
| 12 | 2020 | 1 | |
| 13 | 2020 | 11 | |
| 14 | 2019 | 2 | |
| 15 | 2018 | 6 | |
| 16 | 2018 | 8 | |
| 17 | 2016 | 0 | |
| 18 | 2016 | 76 | |
| 19 | 2013 | 0 | |
| 20 | 1997 | 121 |
About Can Wu
Can Wu is a scholar working on General Materials Science, Electrical and Electronic Engineering, Biomedical Engineering, Human-Computer Interaction and Ceramics and Composites, having authored 23 papers that have together received 287 indexed citations. Recurring topics across this work include Thin-Film Transistor Technologies (8 papers), Advanced Sensor and Energy Harvesting Materials (8 papers), Neuroscience and Neural Engineering (3 papers), Energy Harvesting in Wireless Networks (2 papers), CCD and CMOS Imaging Sensors (2 papers), Radio Frequency Integrated Circuit Design (2 papers), Neural Networks and Reservoir Computing (2 papers) and Advanced Memory and Neural Computing (2 papers). The work is most often cited by research in Electrical and Electronic Engineering (222 citations), Polymers and Plastics (42 citations), Biomedical Engineering (105 citations), Cellular and Molecular Neuroscience (25 citations) and Cognitive Neuroscience (21 citations). Can Wu has collaborated with scholars based in United States, China and Japan. Frequent co-authors include S. Wagner, G. Gu, J. C. Sturm, M. Lu, Stephen R. Forrest, James C. Sturm, Naveen Verma, Warren Rieutort‐Louis, Liechao Huang and Paul Cuff. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Electron Device Letters, Journal of Materials Chemistry C, Integrated ferroelectrics and Nature Electronics.
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.