Mohammed Al-Shabi

498 citations
24 papers · 291 · h-index 9

Impact in

Papers in

Mohammed Al-Shabi

20 papers receiving 275 citations

Peers

Mohammed Al-Shabi
Comparison fields: 5 of 69
  • Computer Networks and Communications 91
  • Artificial Intelligence 124
  • Information Systems 84
  • Computer Vision and Pattern Recognition 58
  • Signal Processing 26
Replace Khaled Alhazmi with:
Khaled Alhazmi Saudi Arabia
Anup Mohan United States
Fahd S. Alharithi Saudi Arabia
Yogesh Kumar India
Dilli Ganesh India
Y. C. A. Padmanabha Reddy India
Nidhi Sindhwani India
Manel Ayadi Saudi Arabia
Gaojuan Fan China
R. Saravanan India
Mohammed Al-Shabi relative to Khaled Alhazmi Saudi Arabia Khaled Alhazmi's profile →
Citations per field
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Khaled Alhazmi · 1×
Citations per year

Countries citing papers authored by Mohammed Al-Shabi

Since Specialization
Citations

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

Fields of papers citing papers by Mohammed Al-Shabi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammed Al-Shabi. 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 Mohammed Al-Shabi. The network helps show where Mohammed Al-Shabi may publish in the future.

Co-authors

The 25 scholars most cited alongside Mohammed Al-Shabi, 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 Mohammed Al-Shabi Line = papers co-authored together Mohammed Al-Shabi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201955
2 201949
3 202246
4 202237
5 202217
6 202216
7 202212
8 202310
9 20229
10 20227
11 20216
12 20066
13 20224
14 20244
15 20234
16 20134
17
Global Behavior of a Fourth Order Rational Difference Equation
20182
18 20231
19 20221
20 20181

About Mohammed Al-Shabi

Mohammed Al-Shabi is a scholar working on Computer Networks and Communications, Artificial Intelligence, Electrical and Electronic Engineering, Information Systems and Computer Vision and Pattern Recognition, having authored 24 papers that have together received 291 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (3 papers), IoT and Edge/Fog Computing (3 papers), Network Security and Intrusion Detection (3 papers), Anomaly Detection Techniques and Applications (3 papers), Advanced Optical Network Technologies (2 papers), Water Quality Monitoring Technologies (2 papers), Blockchain Technology Applications and Security (2 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Computer Networks and Communications (91 citations), Artificial Intelligence (124 citations), Information Systems (84 citations), Computer Vision and Pattern Recognition (58 citations) and Signal Processing (26 citations). Mohammed Al-Shabi has collaborated with scholars based in Saudi Arabia, United Arab Emirates and United Kingdom. Frequent co-authors include Abdulrahman Alqarafi, Fahd N. Al‐Wesabi, Mesfer Al Duhayyim, Nida Nasir, Feras Barneih, Fadwa Alrowais, Nadhem Nemri, Mahmoud Othman, Talal Bonny and Saud S. Alotaibi. Their work appears in journals such as Applied Sciences, Intelligent Systems with Applications, Multimedia Tools and Applications, Wireless Personal Communications 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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