Khaled Ammar

648 citations
17 papers · 286 · h-index 7

Impact in

Papers in

Khaled Ammar

16 papers receiving 281 citations

Peers

Khaled Ammar
Comparison fields: 5 of 29
  • Computer Vision and Pattern Recognition 229
  • Signal Processing 65
  • Information Systems 134
  • Computer Networks and Communications 116
  • Artificial Intelligence 140
Replace Christopher R. Aberger with:
Christopher R. Aberger United States
Oskar van Rest United States
Marcus Paradies Germany
Kaiwei Li China
Yinglong Xia United States
Tim Hegeman Netherlands
Andrew Lamb United States
Mark Callaghan United States
Can Lu Hong Kong
Molham Aref United States
Khaled Ammar relative to Christopher R. Aberger United States Christopher R. Aberger's profile →
Citations per field
00.5×2.7×
Christopher R. Aberger · 1×
Citations per year

Countries citing papers authored by Khaled Ammar

Since Specialization
Citations

This map shows the geographic impact of Khaled Ammar'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 Khaled Ammar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Khaled Ammar more than expected).

Fields of papers citing papers by Khaled Ammar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Khaled Ammar. 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 Khaled Ammar. The network helps show where Khaled Ammar may publish in the future.

Co-authors

The 19 scholars most cited alongside Khaled Ammar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Khaled Ammar Line = papers co-authored together Khaled Ammar links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2014145
2 201851
3 201520
4 201815
5 202110
6 20149
7 20117
8 20166
9 20166
10 20154
11 20133
12 20113
13 20243
14 20192
15 20221
16 20151
17 19880

About Khaled Ammar

Khaled Ammar is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing, Artificial Intelligence and Information Systems, having authored 17 papers that have together received 286 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (7 papers), Data Management and Algorithms (7 papers), Energy Efficient Wireless Sensor Networks (4 papers), Advanced Graph Neural Networks (4 papers), Advanced Database Systems and Queries (3 papers), Distributed Sensor Networks and Detection Algorithms (3 papers), Cloud Computing and Resource Management (2 papers) and Semantic Web and Ontologies (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (229 citations), Signal Processing (65 citations), Information Systems (134 citations), Computer Networks and Communications (116 citations) and Artificial Intelligence (140 citations). Khaled Ammar has collaborated with scholars based in Canada, Austria and Switzerland. Frequent co-authors include M. TAMER ÖZSU, Tianqi Jin, Khuzaima Daudjee, Frank McSherry, Manas Joglekar, Semih Salihoğlu, Mário A. Nascimento, Essam Mansour, Ashraf Aboulnaga and Jimmy Lin. Their work appears in journals such as Proceedings of the VLDB Endowment, Lecture notes in computer science, Integration and Zagazig University Medical Journal.

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.

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