Chen Wu
Impact in
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- Advanced Neural Network Applications
- Hardware and Architecture top 10%
- Parallel Computing and Optimization Techniques
Papers in
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- Topic Modeling 5
- Domain Adaptation and Few-Shot Learning 4
- Machine Learning and ELM 4
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- Microwave Dielectric Ceramics Synthesis 9
- Co-authors
- Lei He (3 shared papers)Yixing Fan (5 shared papers)Jiafeng Guo (5 shared papers)Xueqi Cheng (4 shared papers)Kun Wang (1 shared paper)Hamed Zamani (1 shared paper)Liang Pang (1 shared paper)Yang Liu (1 shared paper)
- Journals
- Ceramics International (5 papers)Journal of Alloys and Compounds (2 papers)physica status solidi (a) (2 papers)ACM Transactions on Information Systems (2 papers)Pattern Recognition Letters (1 paper)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Chen Wu
38 papers receiving 850 citations
Peers
Comparison fields: 5 of 96
- Computer Vision and Pattern Recognition 237
- Hardware and Architecture 76
- Artificial Intelligence 350
- Computational Mathematics 6
- Information Systems 162
Countries citing papers authored by Chen Wu
This map shows the geographic impact of Chen 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 Chen Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chen Wu more than expected).
Fields of papers citing papers by Chen Wu
This network shows the impact of papers produced by Chen 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 Chen Wu. The network helps show where Chen Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Chen 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 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 181 | |
| 2 | 2019 | 113 | |
| 3 | 2015 | 67 | |
| 4 | 2021 | 53 | |
| 5 | 2018 | 40 | |
| 6 | 2022 | 39 | |
| 7 | 2021 | 31 | |
| 8 | 2023 | 30 | |
| 9 | 2022 | 29 | |
| 10 | 2015 | 28 | |
| 11 | 2020 | 24 | |
| 12 | 2022 | 24 | |
| 13 | 2023 | 23 | |
| 14 | 2021 | 21 | |
| 15 | 2019 | 20 | |
| 16 | 2016 | 18 | |
| 17 | 2022 | 18 | |
| 18 | 2023 | 18 | |
| 19 | 2022 | 13 | |
| 20 | 2022 | 11 |
About Chen Wu
Chen Wu is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Materials Chemistry and Biomedical Engineering, having authored 40 papers that have together received 869 indexed citations. Recurring topics across this work include Ferroelectric and Piezoelectric Materials (12 papers), Microwave Dielectric Ceramics Synthesis (9 papers), Dielectric properties of ceramics (5 papers), Topic Modeling (5 papers), Multiferroics and related materials (5 papers), Domain Adaptation and Few-Shot Learning (4 papers), Dielectric materials and actuators (4 papers) and Machine Learning and ELM (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (237 citations), Hardware and Architecture (76 citations), Artificial Intelligence (350 citations), Computational Mathematics (6 citations) and Information Systems (162 citations). Chen Wu has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Lei He, Yixing Fan, Jiafeng Guo, Xueqi Cheng, Kun Wang, Hamed Zamani, Liang Pang, Yang Liu, Qingyao Ai and W. Bruce Croft. Their work appears in journals such as Ceramics International, Journal of Alloys and Compounds, physica status solidi (a), ACM Transactions on Information Systems and Pattern Recognition Letters.
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.