Mourad Khayati
- Artificial Intelligence top 10%
- Signal Processing top 10%
- Computer Networks and Communications
- Management Science and Operations Research
- Computer Vision and Pattern Recognition
- Co-authors
- Philippe Cudré-MaurouxMichael H. BöhlenMichał PiórkowskiJohann GamperJie YangYing ZhangJalel AkaichiMartin Kersten
- Topics
- Time Series Analysis and Forecasting (13 papers)Data Stream Mining Techniques (7 papers)Anomaly Detection Techniques and Applications (7 papers)
- Journals
- Proceedings of the VLDB EndowmentKnowledge and Information SystemsInternational Journal of Intelligent Information and Database Systems
- Partner nations
- SwitzerlandItalyUnited Arab Emirates
In The Last Decade
Mourad Khayati
17 papers receiving 182 citations
Peers
Comparison fields: 5 of 60
- Artificial Intelligence 126
- Signal Processing 88
- Computer Networks and Communications 38
- Management Science and Operations Research 19
- Computer Vision and Pattern Recognition 14
Countries citing papers authored by Mourad Khayati
This map shows the geographic impact of Mourad Khayati'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 Mourad Khayati with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mourad Khayati more than expected).
Fields of papers citing papers by Mourad Khayati
This network shows the impact of papers produced by Mourad Khayati. 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 Mourad Khayati. The network helps show where Mourad Khayati may publish in the future.
Co-authorship network of co-authors of Mourad Khayati
This figure shows the co-authorship network connecting the top 25 collaborators of Mourad Khayati. A scholar is included among the top collaborators of Mourad Khayati 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 Mourad Khayati. Mourad Khayati 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 | 1 | |
| 4 | 6 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 10 | |
| 8 | 18 | |
| 9 | 51 | |
| 10 | 12 | |
| 11 | 12 | |
| 12 | 9 | |
| 13 | 30 | |
| 14 | Missing Value Imputation in Time Series Using Top-k Case Matching. | 1 |
| 15 | 13 | |
| 16 | 7 | |
| 17 | 5 | |
| 18 | 1 | |
| 19 | 3 |
About Mourad Khayati
Mourad Khayati is a scholar working on Computational Mathematics, Signal Processing and Artificial Intelligence, having authored 19 papers that have together received 188 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (13 papers), Data Stream Mining Techniques (7 papers) and Anomaly Detection Techniques and Applications (7 papers). The work is most often cited by research in Signal Processing (88 citations), Artificial Intelligence (126 citations) and Computational Mathematics (2 citations). Mourad Khayati has collaborated with scholars based in Switzerland, Italy and United Arab Emirates. Frequent co-authors include Philippe Cudré-Mauroux, Michael H. Böhlen, Michał Piórkowski, Johann Gamper, Jie Yang, Ying Zhang, Jalel Akaichi, Martin Kersten, Manfred Hauswirth and Djellel Difallah. Their work appears in journals such as Proceedings of the VLDB Endowment, Knowledge and Information Systems and International Journal of Intelligent Information and Database Systems.
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.