Ayman E. Khedr

64 papers receiving 591 citations

Peers

Ayman E. Khedr
Comparison fields: 5 of 80
  • Computer Science Applications 79
  • Management Information Systems 86
  • Management Science and Operations Research 95
  • Information Systems 166
  • Artificial Intelligence 231
Replace Amira M. Idrees with:
Amira M. Idrees Egypt
Maryam Khanian Najafabadi Australia
Abba Suganda Girsang Indonesia
Philip Achimugu Nigeria
Anne Persson Sweden
Rommel N. Carvalho Brazil
Isabelle Comyn-Wattiau France
Riyaz Sikora United States
Pornpit Wongthongtham Australia
Rajendra Sonar India
Ayman E. Khedr relative to Amira M. Idrees Egypt Amira M. Idrees's profile →
Citations per field
00.5×4.5×
Amira M. Idrees · 1×
Citations per year

Countries citing papers authored by Ayman E. Khedr

Since Specialization
Citations

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

Fields of papers citing papers by Ayman E. Khedr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ayman E. Khedr. 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 Ayman E. Khedr. The network helps show where Ayman E. Khedr may publish in the future.

Co-authors

The 23 scholars most cited alongside Ayman E. Khedr, 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 Ayman E. Khedr Line = papers co-authored together Ayman E. Khedr links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017108
2 201640
3 201528
4 201726
5 201725
6 202323
7 201721
8 201721
9 201720
10 201518
11 202216
12 201515
13 202114
14 201914
15 201514
16 201311
17 201711
18 202110
19 202110
20 201610

About Ayman E. Khedr

Ayman E. Khedr is a scholar working on Information Systems, Artificial Intelligence, Management Information Systems, Computer Networks and Communications and Management Science and Operations Research, having authored 68 papers that have together received 620 indexed citations. Recurring topics across this work include Big Data and Business Intelligence (12 papers), Data Mining Algorithms and Applications (7 papers), Online Learning and Analytics (6 papers), Artificial Intelligence in Healthcare (5 papers), Cloud Computing and Resource Management (5 papers), IoT and Edge/Fog Computing (5 papers), Data Stream Mining Techniques (5 papers) and Text and Document Classification Technologies (5 papers). The work is most often cited by research in Computer Science Applications (79 citations), Management Information Systems (86 citations), Management Science and Operations Research (95 citations), Information Systems (166 citations) and Artificial Intelligence (231 citations). Ayman E. Khedr has collaborated with scholars based in Egypt, Saudi Arabia and Canada. Frequent co-authors include Amira M. Idrees, Bryan A. Tolson, Ashraf Darwish, Khalid M. Hosny, Laila A. Abd-Elmegid, Mohamed Meselhy Eltoukhy, Ahmed Sharaf Eldin, Abdulwahab Ali Almazroi, Hatem Abdul-Kader and Mona Nasr. Their work appears in journals such as PeerJ Computer Science, Journal of Southwest Jiaotong University, IEEE Access, Alexandria Engineering Journal and Computers, materials & continua/Computers, materials & continua (Print).

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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