Mohammed E. Fouda

3.6k citations
173 papers · 2.6k · h-index 28

Impact in

Papers in

Mohammed E. Fouda

158 papers receiving 2.5k citations

Peers

Mohammed E. Fouda
Comparison fields: 5 of 90
  • Cellular and Molecular Neuroscience 619
  • Electrical and Electronic Engineering 2.0k
  • Statistical and Nonlinear Physics 352
  • Modeling and Simulation 116
  • Cognitive Neuroscience 360
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Citations per year

Countries citing papers authored by Mohammed E. Fouda

Since Specialization
Citations

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

Fields of papers citing papers by Mohammed E. Fouda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 173 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021179
2 2018137
3 2013122
4 2016107
5 201595
6 201291
7 201758
8 202250
9 201850
10 201846
11 201445
12 201545
13 201343
14 201342
15 201942
16 202141
17 202038
18 201836
19 202136
20 201635

About Mohammed E. Fouda

Mohammed E. Fouda is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Artificial Intelligence, Cognitive Neuroscience and Automotive Engineering, having authored 173 papers that have together received 2.6k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (96 papers), Ferroelectric and Negative Capacitance Devices (41 papers), Neuroscience and Neural Engineering (32 papers), Neural dynamics and brain function (23 papers), Advanced Battery Technologies Research (19 papers), Neural Networks and Reservoir Computing (14 papers), CCD and CMOS Imaging Sensors (14 papers) and Advanced Control Systems Design (13 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (619 citations), Electrical and Electronic Engineering (2.0k citations), Statistical and Nonlinear Physics (352 citations), Modeling and Simulation (116 citations) and Cognitive Neuroscience (360 citations). Mohammed E. Fouda has collaborated with scholars based in United States, Egypt and Saudi Arabia. Frequent co-authors include Ahmed G. Radwan, Ahmed M. Eltawil, Ahmed S. Elwakil, Anis Allagui, K. Saláma, Fadi Kurdahi, Wenzhe Guo, Lobna A. Said, Abdullah G. Alharbi and Masud H. Chowdhury. Their work appears in journals such as International Journal of Circuit Theory and Applications, IEEE Access, IEEE Transactions on Circuits & Systems II Express Briefs, Electronics and Journal of The Electrochemical Society.

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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