Ahmed Kattan
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Computer Networks and Communications top 10%
- Computational Theory and Mathematics top 10%
- Co-authors
- Muhammad ArifSheikh Iqbal AhamedEdgar GalvánMohsin BilalYew-Soon OngRiccardo PoliMichael O’NeillShaheen Fatima
- Topics
- Evolutionary Algorithms and Applications (18 papers)Metaheuristic Optimization Algorithms Research (15 papers)Advanced Multi-Objective Optimization Algorithms (8 papers)
- Partner nations
- Saudi ArabiaUnited KingdomIreland
In The Last Decade
Ahmed Kattan
28 papers receiving 421 citations
Peers
Comparison fields: 5 of 86
- Artificial Intelligence 188
- Computer Vision and Pattern Recognition 147
- Biomedical Engineering 120
- Computer Networks and Communications 67
- Computational Theory and Mathematics 56
Countries citing papers authored by Ahmed Kattan
This map shows the geographic impact of Ahmed Kattan'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 Ahmed Kattan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ahmed Kattan more than expected).
Fields of papers citing papers by Ahmed Kattan
This network shows the impact of papers produced by Ahmed Kattan. 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 Ahmed Kattan. The network helps show where Ahmed Kattan may publish in the future.
Co-authorship network of co-authors of Ahmed Kattan
This figure shows the co-authorship network connecting the top 25 collaborators of Ahmed Kattan. A scholar is included among the top collaborators of Ahmed Kattan 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 Ahmed Kattan. Ahmed Kattan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 30 | |
| 3 | 4 | |
| 4 | 13 | |
| 5 | 4 | |
| 6 | 9 | |
| 7 | 6 | |
| 8 | 84 | |
| 9 | 21 | |
| 10 | 2 | |
| 11 | 12 | |
| 12 | 74 | |
| 13 | 1 | |
| 14 | 6 | |
| 15 | 4 | |
| 16 | 20 | |
| 17 | 26 | |
| 18 | 10 | |
| 19 | 23 | |
| 20 | 11 |
About Ahmed Kattan
Ahmed Kattan is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Transportation, having authored 30 papers that have together received 444 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (18 papers), Metaheuristic Optimization Algorithms Research (15 papers) and Advanced Multi-Objective Optimization Algorithms (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (147 citations), Artificial Intelligence (188 citations) and Transportation (24 citations). Ahmed Kattan has collaborated with scholars based in Saudi Arabia, United Kingdom and Ireland. Frequent co-authors include Muhammad Arif, Sheikh Iqbal Ahamed, Edgar Galván, Mohsin Bilal, Yew-Soon Ong, Riccardo Poli, Michael O’Neill, Shaheen Fatima, Anthony Brabazon and Francisco Sepúlveda. Their work appears in journals such as PLoS ONE, Information Sciences and Journal of Network and Computer Applications.
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.