George H. Chen
- Artificial Intelligence top 5%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Computer Vision and Pattern Recognition top 10%
- Control and Systems Engineering
- Co-authors
- Devavrat ShahYue ZhaoXiyang HuNicola BottaCezar IonescuZheng LiPedro FerreiraMichael D. Smith
- Topics
- Anomaly Detection Techniques and Applications (4 papers)Sparse and Compressive Sensing Techniques (2 papers)Time Series Analysis and Forecasting (2 papers)
- Journals
- Journal of Marketing ResearchIEEE Transactions on Knowledge and Data EngineeringProceedings of the VLDB Endowment
- Partner nations
- United StatesGermanyMexico
In The Last Decade
George H. Chen
15 papers receiving 491 citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Artificial Intelligence 278
- Computer Networks and Communications 93
- Signal Processing 83
- Computer Vision and Pattern Recognition 69
- Control and Systems Engineering 62
Countries citing papers authored by George H. Chen
This map shows the geographic impact of George H. Chen'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 George H. Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George H. Chen more than expected).
Fields of papers citing papers by George H. Chen
This network shows the impact of papers produced by George H. Chen. 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 George H. Chen. The network helps show where George H. Chen may publish in the future.
Co-authorship network of co-authors of George H. Chen
This figure shows the co-authorship network connecting the top 25 collaborators of George H. Chen. A scholar is included among the top collaborators of George H. Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with George H. Chen. George H. Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 23 | |
| 4 | ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functionsbreakdown → | 206 |
| 5 | 30 | |
| 6 | 2 | |
| 7 | 7 | |
| 8 | 56 | |
| 9 | 7 | |
| 10 | 68 | |
| 11 | 43 | |
| 12 | 34 | |
| 13 | 2 | |
| 14 | A Latent Source Model for Online Time Series Classification | 1 |
| 15 | 25 | |
| 16 | 3 | |
| 17 | 2 |
About George H. Chen
George H. Chen is a scholar working on Computer Vision and Pattern Recognition, Statistics and Probability and Media Technology, having authored 17 papers that have together received 509 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (4 papers), Sparse and Compressive Sensing Techniques (2 papers) and Time Series Analysis and Forecasting (2 papers). The work is most often cited by research in Artificial Intelligence (278 citations), Signal Processing (83 citations) and Computer Networks and Communications (93 citations). George H. Chen has collaborated with scholars based in United States, Germany and Mexico. Frequent co-authors include Devavrat Shah, Yue Zhao, Xiyang Hu, Nicola Botta, Cezar Ionescu, Zheng Li, Pedro Ferreira, Michael D. Smith, Stanislav Nikolov and Zheng Li. Their work appears in journals such as Journal of Marketing Research, IEEE Transactions on Knowledge and Data Engineering and Proceedings of the VLDB Endowment.
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.