Mamoun Awad
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Signal Processing top 5%
- Co-authors
- Latifur KhanBhavani ThuraisinghamIssa KhalilLei WangSalah BouktifAli FiazFarag SallabiKhaled Shuaib
- Topics
- IoT and Edge/Fog Computing (3 papers)Recommender Systems and Techniques (3 papers)Stock Market Forecasting Methods (3 papers)
- Journals
- IEEE AccessSustainabilityIEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
- Partner nations
- United Arab EmiratesUnited StatesPakistan
In The Last Decade
Mamoun Awad
28 papers receiving 755 citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 372
- Computer Networks and Communications 369
- Computer Vision and Pattern Recognition 219
- Information Systems 169
- Signal Processing 161
Countries citing papers authored by Mamoun Awad
This map shows the geographic impact of Mamoun Awad'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 Mamoun Awad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mamoun Awad more than expected).
Fields of papers citing papers by Mamoun Awad
This network shows the impact of papers produced by Mamoun Awad. 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 Mamoun Awad. The network helps show where Mamoun Awad may publish in the future.
Co-authorship network of co-authors of Mamoun Awad
This figure shows the co-authorship network connecting the top 25 collaborators of Mamoun Awad. A scholar is included among the top collaborators of Mamoun Awad 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 Mamoun Awad. Mamoun Awad 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 | 1 | |
| 3 | 7 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 28 | |
| 10 | 4 | |
| 11 | 19 | |
| 12 | 78 | |
| 13 | 2 | |
| 14 | 15 | |
| 15 | 0 | |
| 16 | 1 | |
| 17 | 6 | |
| 18 | 40 | |
| 19 | 290 | |
| 20 | 35 |
About Mamoun Awad
Mamoun Awad is a scholar working on Computer Networks and Communications, Human-Computer Interaction and Management Science and Operations Research, having authored 31 papers that have together received 838 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (3 papers), Recommender Systems and Techniques (3 papers) and Stock Market Forecasting Methods (3 papers). The work is most often cited by research in Computer Networks and Communications (369 citations), Signal Processing (161 citations) and Artificial Intelligence (372 citations). Mamoun Awad has collaborated with scholars based in United Arab Emirates, United States and Pakistan. Frequent co-authors include Latifur Khan, Bhavani Thuraisingham, Issa Khalil, Lei Wang, Salah Bouktif, Ali Fiaz, Farag Sallabi, Khaled Shuaib, Faisal Naeem and I‐Ling Yen. Their work appears in journals such as IEEE Access, Sustainability and IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics).
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.