Alaa Khamis
- Artificial Intelligence top 1%
- Computer Networks and Communications top 2%
- Computer Vision and Pattern Recognition top 1%
- Control and Systems Engineering top 2%
- Aerospace Engineering top 2%
- Co-authors
- Bahador KhaleghiFakhreddine KarraySaiedeh RazaviAhmed HusseinAhmed ElmogyMohamed S. KamelAhmad Taher AzarHoward Li
- Topics
- Modular Robots and Swarm Intelligence (11 papers)Robotics and Automated Systems (9 papers)Optimization and Search Problems (9 papers)
- Cited by
- Computer Vision and Pattern RecognitionComputer Networks and CommunicationsArtificial Intelligence
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
In The Last Decade
Alaa Khamis
86 papers receiving 3.0k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Artificial Intelligence 948
- Computer Networks and Communications 757
- Computer Vision and Pattern Recognition 731
- Control and Systems Engineering 646
- Aerospace Engineering 461
Countries citing papers authored by Alaa Khamis
This map shows the geographic impact of Alaa Khamis'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 Alaa Khamis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alaa Khamis more than expected).
Fields of papers citing papers by Alaa Khamis
This network shows the impact of papers produced by Alaa Khamis. 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 Alaa Khamis. The network helps show where Alaa Khamis may publish in the future.
Co-authorship network of co-authors of Alaa Khamis
This figure shows the co-authorship network connecting the top 25 collaborators of Alaa Khamis. A scholar is included among the top collaborators of Alaa Khamis 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 Alaa Khamis. Alaa Khamis 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 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 3 | |
| 7 | Drone Deep Reinforcement Learning: A Reviewbreakdown → | 192 |
| 8 | 77 | |
| 9 | 11 | |
| 10 | 67 | |
| 11 | 52 | |
| 12 | 23 | |
| 13 | 5 | |
| 14 | 62 | |
| 15 | 5 | |
| 16 | Minesweepers: Towards a Landmine-Free Egypt, an Outdoor Humanitarian Demining Robotic Competition | 1 |
| 17 | 12 | |
| 18 | 13 | |
| 19 | 26 | |
| 20 | 4 |
About Alaa Khamis
Alaa Khamis is a scholar working on Computer Networks and Communications, Control and Systems Engineering and Industrial and Manufacturing Engineering, having authored 89 papers that have together received 3.1k indexed citations. Recurring topics across this work include Modular Robots and Swarm Intelligence (11 papers), Robotics and Automated Systems (9 papers) and Optimization and Search Problems (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (731 citations), Computer Networks and Communications (757 citations) and Artificial Intelligence (948 citations). Alaa Khamis has collaborated with scholars based in Canada, Egypt and Spain. Frequent co-authors include Bahador Khaleghi, Fakhreddine Karray, Saiedeh Razavi, Ahmed Hussein, Ahmed Elmogy, Mohamed S. Kamel, Ahmad Taher Azar, Howard Li, Miguel Á. Salichs and Khalid Elgazzar. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.
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.