Ghaith Manita
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics top 10%
- Information Systems
- Electrical and Electronic Engineering
- Co-authors
- Ouajdi KorbaaAmit ChhabraSeyedali MirjaliliIkbal ChaiebAbdelkader MamiMohamed LimamYaning XiaoFatma A. Hashim
- Topics
- Metaheuristic Optimization Algorithms Research (18 papers)Evolutionary Algorithms and Applications (12 papers)Data Mining Algorithms and Applications (4 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsIndustrial and Manufacturing Engineering
In The Last Decade
Ghaith Manita
27 papers receiving 272 citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 153
- Computer Vision and Pattern Recognition 47
- Computational Theory and Mathematics 45
- Information Systems 30
- Electrical and Electronic Engineering 28
Countries citing papers authored by Ghaith Manita
This map shows the geographic impact of Ghaith Manita'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 Ghaith Manita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ghaith Manita more than expected).
Fields of papers citing papers by Ghaith Manita
This network shows the impact of papers produced by Ghaith Manita. 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 Ghaith Manita. The network helps show where Ghaith Manita may publish in the future.
Co-authorship network of co-authors of Ghaith Manita
This figure shows the co-authorship network connecting the top 25 collaborators of Ghaith Manita. A scholar is included among the top collaborators of Ghaith Manita 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 Ghaith Manita. Ghaith Manita 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 | 2 | |
| 3 | 14 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 13 | |
| 7 | 1 | |
| 8 | 81 | |
| 9 | 29 | |
| 10 | 2 | |
| 11 | 12 | |
| 12 | 5 | |
| 13 | 13 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 9 | |
| 17 | 8 | |
| 18 | 26 | |
| 19 | 5 | |
| 20 | 1 |
About Ghaith Manita
Ghaith Manita is a scholar working on Artificial Intelligence, Software and Industrial and Manufacturing Engineering, having authored 31 papers that have together received 283 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (18 papers), Evolutionary Algorithms and Applications (12 papers) and Data Mining Algorithms and Applications (4 papers). The work is most often cited by research in Artificial Intelligence (153 citations), Computational Theory and Mathematics (45 citations) and Industrial and Manufacturing Engineering (23 citations). Ghaith Manita has collaborated with scholars based in Tunisia, India and Australia. Frequent co-authors include Ouajdi Korbaa, Amit Chhabra, Seyedali Mirjalili, Ikbal Chaieb, Abdelkader Mami, Mohamed Limam, Yaning Xiao, Fatma A. Hashim, Mohamed Ali Hajjaji and Reham R. Mostafa. Their work appears in journals such as International Journal of Production Research, Applied Soft Computing and Neural Computing and 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.