Quchen Fu
Impact in
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- Speech and Audio Processing
- Music and Audio Processing
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- Artificial Intelligence in Healthcare and Education
Papers in
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- Speech Recognition and Synthesis 4
- Natural Language Processing Techniques 1
- Computational Physics and Python Applications 1
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- Speech and Audio Processing 3
- Music and Audio Processing 3
- Co-authors
- Jules White (7 shared papers)Douglas C. Schmidt (7 shared papers)Jesse Spencer-Smith (1 shared paper)Jian Feng (1 shared paper)Yu Yao (1 shared paper)Peng Zhang (1 shared paper)Li Ran (1 shared paper)Cheng Jiang (1 shared paper)
- Journals
- Computers in Biology and Medicine (1 paper)ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (1 paper)2022 26th International Conference on Pattern Recognition (ICPR) (1 paper)ACM SIGAda Ada Letters (1 paper)Interspeech 2022 (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Quchen Fu
8 papers receiving 55 citations
Peers
Comparison fields: 5 of 40
- Signal Processing 30
- Health Informatics 3
- Artificial Intelligence 33
- Computer Vision and Pattern Recognition 20
- Software 3
Countries citing papers authored by Quchen Fu
This map shows the geographic impact of Quchen Fu'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 Quchen Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quchen Fu more than expected).
Fields of papers citing papers by Quchen Fu
This network shows the impact of papers produced by Quchen Fu. 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 Quchen Fu. The network helps show where Quchen Fu may publish in the future.
Co-authors
The 8 scholars most cited alongside Quchen Fu, 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 | 21 | |
| 2 | 2024 | 15 | |
| 3 | 2022 | 9 | |
| 4 | 2021 | 8 | |
| 5 | 2023 | 5 | |
| 6 | 2021 | 2 | |
| 7 | 2017 | 1 | |
| 8 | 2022 | 1 |
About Quchen Fu
Quchen Fu is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Computer Vision and Pattern Recognition and Health Informatics, having authored 8 papers that have together received 62 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (4 papers), Speech and Audio Processing (3 papers), Music and Audio Processing (3 papers), Natural Language Processing Techniques (1 paper), Computational Physics and Python Applications (1 paper), Dysphagia Assessment and Management (1 paper), Advanced Measurement and Metrology Techniques (1 paper) and Artificial Intelligence in Healthcare and Education (1 paper). The work is most often cited by research in Signal Processing (30 citations), Health Informatics (3 citations), Artificial Intelligence (33 citations), Computer Vision and Pattern Recognition (20 citations) and Software (3 citations). Quchen Fu has collaborated with scholars based in United States and China. Frequent co-authors include Jules White, Douglas C. Schmidt, Jesse Spencer-Smith, Jian Feng, Yu Yao, Peng Zhang, Li Ran and Cheng Jiang. Their work appears in journals such as Computers in Biology and Medicine, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 26th International Conference on Pattern Recognition (ICPR), ACM SIGAda Ada Letters and Interspeech 2022.
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.