Mohammad Al‐Shabi

2.8k citations
180 papers · 1.9k · h-index 20

Impact in

Papers in

Mohammad Al‐Shabi

156 papers receiving 1.8k citations

Peers

Mohammad Al‐Shabi
Comparison fields: 5 of 115
  • Energy Engineering and Power Technology 101
  • Control and Systems Engineering 575
  • Automotive Engineering 166
  • Renewable Energy, Sustainability and the Environment 217
  • Artificial Intelligence 457
Replace N.K. M’Sirdi with:
N.K. M’Sirdi France
Žarko Ćojbašić Serbia
Huan Long China
Alberto Pliego Marugán Spain
Mauro Venturini Italy
Abdelhamid Rabhi France
Gianluca Ippoliti Italy
Ekaitz Zulueta Spain
Paweł Ocłoń Poland
Debashisha Jena India
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Citations per field
00.5×6.3×
N.K. M’Sirdi · 1×
Citations per year

Countries citing papers authored by Mohammad Al‐Shabi

Since Specialization
Citations

This map shows the geographic impact of Mohammad 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 Mohammad 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 Mohammad Al‐Shabi more than expected).

Fields of papers citing papers by Mohammad Al‐Shabi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mohammad 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 Mohammad Al‐Shabi Line = papers co-authored together Mohammad 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 180 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021205
2 2020167
3 202374
4 201370
5 201268
6 201955
7 202254
8 202253
9 202047
10 202345
11 202032
12 201131
13 202131
14 201927
15 202026
16 202125
17 202025
18 202124
19 202221
20 202319

About Mohammad Al‐Shabi

Mohammad Al‐Shabi is a scholar working on Control and Systems Engineering, Artificial Intelligence, Aerospace Engineering, Electrical and Electronic Engineering and Mechanical Engineering, having authored 180 papers that have together received 1.9k indexed citations. Recurring topics across this work include Target Tracking and Data Fusion in Sensor Networks (39 papers), Fault Detection and Control Systems (32 papers), Inertial Sensor and Navigation (15 papers), Adaptive Control of Nonlinear Systems (14 papers), Hydraulic and Pneumatic Systems (14 papers), Structural Health Monitoring Techniques (13 papers), Microgrid Control and Optimization (11 papers) and Robotic Path Planning Algorithms (11 papers). The work is most often cited by research in Energy Engineering and Power Technology (101 citations), Control and Systems Engineering (575 citations), Automotive Engineering (166 citations), Renewable Energy, Sustainability and the Environment (217 citations) and Artificial Intelligence (457 citations). Mohammad Al‐Shabi has collaborated with scholars based in United Arab Emirates, Canada and United States. Frequent co-authors include S. Andrew Gadsden, Mamdouh El Haj Assad, A. Elnady, Saeid Habibi, D.H. Jamali, Abolfazl Ahmadi, M.A. Ehyaei, Ali Ahmed Adam Ismail, Maâmar Bettayeb and Ramesh C. Bansal. Their work appears in journals such as Sensors, IEEE Signal Processing Letters, IEEE Access, IEEE Transactions on Instrumentation and Measurement and Energies.

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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