Mohamed Elfeky
- Artificial Intelligence top 5%
- Signal Processing top 2%
- Information Systems top 2%
- Management Science and Operations Research top 2%
- Computer Networks and Communications top 5%
- Co-authors
- Ahmed K. ElmagarmidWalid G. ArefVassilios S. VerykiosM.E. El-HawaryGeorge V. MoustakidesThanaa M. GhanemPedro J. MorenoMohamed Y. Eltabakh
- Topics
- Music and Audio Processing (5 papers)Time Series Analysis and Forecasting (5 papers)Data Management and Algorithms (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Knowledge and Data EngineeringHeliyon
- Partner nations
- United StatesIndiaGreece
In The Last Decade
Mohamed Elfeky
17 papers receiving 706 citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 452
- Signal Processing 295
- Information Systems 292
- Management Science and Operations Research 243
- Computer Networks and Communications 200
Countries citing papers authored by Mohamed Elfeky
This map shows the geographic impact of Mohamed Elfeky'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 Mohamed Elfeky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohamed Elfeky more than expected).
Fields of papers citing papers by Mohamed Elfeky
This network shows the impact of papers produced by Mohamed Elfeky. 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 Mohamed Elfeky. The network helps show where Mohamed Elfeky may publish in the future.
Co-authorship network of co-authors of Mohamed Elfeky
This figure shows the co-authorship network connecting the top 25 collaborators of Mohamed Elfeky. A scholar is included among the top collaborators of Mohamed Elfeky 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 Mohamed Elfeky. Mohamed Elfeky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 7 | |
| 3 | 9 | |
| 4 | 18 | |
| 5 | 9 | |
| 6 | 88 | |
| 7 | 17 | |
| 8 | 65 | |
| 9 | 151 | |
| 10 | 80 | |
| 11 | 56 | |
| 12 | 184 | |
| 13 | Record Linkage: A Machine Learning Approach, A Toolbox, and a Digital Government Web Service | 10 |
| 14 | 60 | |
| 15 | A Stream Database Server for Sensor Applications | 1 |
| 16 | On the Accuracy and Completeness of the Record Matching Process. | 12 |
| 17 | Incremental Mining of Partial Periodic Patterns in Time-Series Databases | 2 |
About Mohamed Elfeky
Mohamed Elfeky is a scholar working on Signal Processing, Artificial Intelligence and Management Science and Operations Research, having authored 17 papers that have together received 779 indexed citations. Recurring topics across this work include Music and Audio Processing (5 papers), Time Series Analysis and Forecasting (5 papers) and Data Management and Algorithms (5 papers). The work is most often cited by research in Signal Processing (295 citations), Management Science and Operations Research (243 citations) and Artificial Intelligence (452 citations). Mohamed Elfeky has collaborated with scholars based in United States, India and Greece. Frequent co-authors include Ahmed K. Elmagarmid, Walid G. Aref, Vassilios S. Verykios, M.E. El-Hawary, George V. Moustakides, Thanaa M. Ghanem, Pedro J. Moreno, Mohamed Y. Eltabakh, Moustafa A. Hammad and Ann Christine Catlin. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Knowledge and Data Engineering and Heliyon.
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.