Youxi Wu
Impact in
- Information Systems top 1%
- Data Mining Algorithms and Applications
- Signal Processing top 2%
- Time Series Analysis and Forecasting
- Data Management and Algorithms
Papers in
-
- Algorithms and Data Compression 20
- Imbalanced Data Classification Techniques 10
-
- Data Mining Algorithms and Applications 38
- Co-authors
- Xindong Wu (39 shared papers)Lei Guo (47 shared papers)Yan Li (25 shared papers)Xingquan Zhu (10 shared papers)He Jiang (11 shared papers)Philippe Fournier‐Viger (15 shared papers)Fang Yao (5 shared papers)Fan Min (7 shared papers)
- Journals
- Applied Intelligence (8 papers)Neurocomputing (6 papers)IEEE Access (5 papers)IEEE Transactions on Knowledge and Data Engineering (5 papers)Information Sciences (4 papers)
- Partner nations
- ChinaUnited StatesPortugal
In The Last Decade
Youxi Wu
106 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 122
- Information Systems 720
- Signal Processing 343
- Computational Theory and Mathematics 387
- Artificial Intelligence 618
- Automotive Engineering 109
Countries citing papers authored by Youxi Wu
This map shows the geographic impact of Youxi 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 Youxi Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Youxi Wu more than expected).
Fields of papers citing papers by Youxi Wu
This network shows the impact of papers produced by Youxi 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 Youxi Wu. The network helps show where Youxi Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Youxi 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 110 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 104 | |
| 2 | 2017 | 74 | |
| 3 | 2011 | 64 | |
| 4 | 2010 | 60 | |
| 5 | 2020 | 58 | |
| 6 | 2014 | 52 | |
| 7 | 2021 | 52 | |
| 8 | 2021 | 49 | |
| 9 | 2016 | 46 | |
| 10 | 2016 | 41 | |
| 11 | 2011 | 41 | |
| 12 | 2021 | 41 | |
| 13 | 2021 | 41 | |
| 14 | 2021 | 39 | |
| 15 | 2021 | 34 | |
| 16 | 2022 | 29 | |
| 17 | 2022 | 26 | |
| 18 | 2016 | 26 | |
| 19 | 2022 | 24 | |
| 20 | 2023 | 23 |
About Youxi Wu
Youxi Wu is a scholar working on Artificial Intelligence, Information Systems, Electrical and Electronic Engineering, Signal Processing and Computational Theory and Mathematics, having authored 110 papers that have together received 1.5k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (38 papers), Rough Sets and Fuzzy Logic (22 papers), Algorithms and Data Compression (20 papers), Advanced Memory and Neural Computing (19 papers), Neural dynamics and brain function (19 papers), Data Management and Algorithms (14 papers), Time Series Analysis and Forecasting (13 papers) and Imbalanced Data Classification Techniques (10 papers). The work is most often cited by research in Information Systems (720 citations), Signal Processing (343 citations), Computational Theory and Mathematics (387 citations), Artificial Intelligence (618 citations) and Automotive Engineering (109 citations). Youxi Wu has collaborated with scholars based in China, United States and Portugal. Frequent co-authors include Xindong Wu, Lei Guo, Yan Li, Xingquan Zhu, He Jiang, Philippe Fournier‐Viger, Fang Yao, Fan Min, Guizhi Xu and Fei Ding. Their work appears in journals such as Applied Intelligence, Neurocomputing, IEEE Access, IEEE Transactions on Knowledge and Data Engineering and Information Sciences.
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.