Yifan Gong
- Signal Processing top 0.2%
- Speech and Audio Processing 68
- Music and Audio Processing 56
- Artificial Intelligence top 0.5%
- Speech Recognition and Synthesis 91
- Natural Language Processing Techniques 17
- Topic Modeling 8
- Neural Networks and Applications 7
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- Advanced Data Compression Techniques 7
- Advanced Neural Network Applications 7
- Computational Mathematics top 10%
- Hardware and Architecture top 10%
- Journals
- SHILAP Revista de lepidopterología (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Sensors (1 paper)
- Partner nations
- United StatesFranceUnited Kingdom
In The Last Decade
Yifan Gong
116 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Signal Processing 1.6k
- Artificial Intelligence 2.1k
- Computer Vision and Pattern Recognition 499
- Computational Mathematics 13
- Hardware and Architecture 44
Countries citing papers authored by Yifan Gong
This map shows the geographic impact of Yifan Gong'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 Yifan Gong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yifan Gong more than expected).
Fields of papers citing papers by Yifan Gong
This network shows the impact of papers produced by Yifan Gong. 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 Yifan Gong. The network helps show where Yifan Gong may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yifan Gong, 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 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 2 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 0 | |
| 9 | 2022 | 5 | |
| 10 | 2022 | 6 | |
| 11 | 2021 | 42 | |
| 12 | 2021 | 26 | |
| 13 | 2021 | 9 | |
| 14 | A Privacy-Preserving DNN Pruning and Mobile Acceleration Framework. | 2020 | 2 |
| 15 | 2019 | 21 | |
| 16 | 2015 | 91 | |
| 17 | 2015 | 72 | |
| 18 | 2014 | 2 | |
| 19 | 2013 | 250 | |
| 20 | 2009 | 76 |
About Yifan Gong
Yifan Gong is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 124 papers that have together received 2.7k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (91 papers), Speech and Audio Processing (68 papers), Music and Audio Processing (56 papers), Natural Language Processing Techniques (17 papers), Topic Modeling (8 papers), Advanced Data Compression Techniques (7 papers), Advanced Neural Network Applications (7 papers) and Neural Networks and Applications (7 papers). The work is most often cited by research in Signal Processing (1.6k citations), Artificial Intelligence (2.1k citations) and Computer Vision and Pattern Recognition (499 citations). Yifan Gong has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Jinyu Li, Jui-Ting Huang, Dong Yu, Jian Xue, Rui Zhao, Alex Acero, Li Deng, Zhong Meng, Yong Zhao and Michael L. Seltzer. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Sensors.
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.