Mingxi Wu
Impact in
- Signal Processing top 2%
- Data Management and Algorithms
- Time Series Analysis and Forecasting
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- Advanced Database Systems and Queries
- Network Security and Intrusion Detection
Papers in
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- Advanced Database Systems and Queries 9
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- Anomaly Detection Techniques and Applications 7
- Co-authors
- Christopher Jermaine (5 shared papers)Sanjay Ranka (4 shared papers)Luis L. Perez (3 shared papers)Fei Xu (3 shared papers)Peter J. Haas (2 shared papers)Chris Jermaine (7 shared papers)Alin Deutsch (2 shared papers)John G. Gums (2 shared papers)
- Journals
- Proceedings of the VLDB Endowment (2 papers)ACM Transactions on Database Systems (2 papers)The VLDB Journal (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)ACM Transactions on Knowledge Discovery from Data (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Mingxi Wu
22 papers receiving 799 citations
Peers
Comparison fields: 5 of 65
- Signal Processing 361
- Computer Networks and Communications 443
- Artificial Intelligence 569
- Management Science and Operations Research 91
- Computer Vision and Pattern Recognition 110
Countries citing papers authored by Mingxi Wu
This map shows the geographic impact of Mingxi 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 Mingxi Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingxi Wu more than expected).
Fields of papers citing papers by Mingxi Wu
This network shows the impact of papers produced by Mingxi 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 Mingxi Wu. The network helps show where Mingxi Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingxi 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 241 | |
| 2 | 2008 | 197 | |
| 3 | 2007 | 97 | |
| 4 | 2022 | 58 | |
| 5 | 2006 | 55 | |
| 6 | 2011 | 31 | |
| 7 | 2009 | 28 | |
| 8 | 2022 | 26 | |
| 9 | 2020 | 23 | |
| 10 | 2013 | 18 | |
| 11 | A Bayesian method for guessing the extreme values in a data set | 2007 | 17 |
| 12 | 2008 | 12 | |
| 13 | 2022 | 10 | |
| 14 | 1992 | 9 | |
| 15 | 2003 | 8 | |
| 16 | 2009 | 6 | |
| 17 | 2011 | 6 | |
| 18 | 2010 | 5 | |
| 19 | 2025 | 4 | |
| 20 | 2022 | 4 |
About Mingxi Wu
Mingxi Wu is a scholar working on Computer Networks and Communications, Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition and Epidemiology, having authored 23 papers that have together received 858 indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (9 papers), Data Management and Algorithms (8 papers), Anomaly Detection Techniques and Applications (7 papers), Time Series Analysis and Forecasting (5 papers), Data-Driven Disease Surveillance (4 papers), Graph Theory and Algorithms (4 papers), Advanced Statistical Methods and Models (3 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Signal Processing (361 citations), Computer Networks and Communications (443 citations), Artificial Intelligence (569 citations), Management Science and Operations Research (91 citations) and Computer Vision and Pattern Recognition (110 citations). Mingxi Wu has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Christopher Jermaine, Sanjay Ranka, Luis L. Perez, Fei Xu, Peter J. Haas, Chris Jermaine, Alin Deutsch, John G. Gums, Yu Xu and Oskar van Rest. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM Transactions on Database Systems, The VLDB Journal, IEEE Transactions on Knowledge and Data Engineering and ACM Transactions on Knowledge Discovery from Data.
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.