Ibrahim Gad

45 papers receiving 1.2k citations

Peers

Ibrahim Gad
Comparison fields: 5 of 134
  • Modeling and Simulation 162
  • Environmental Engineering 273
  • Health Information Management 76
  • Health Informatics 16
  • Health, Toxicology and Mutagenesis 160
Replace Abdelkader Dairi with:
Abdelkader Dairi Algeria
Mohsen Ahmadi Iran
Ramon Gomes da Silva Brazil
Abbas Sharifi Iran
Farah Shahid Pakistan
Muhammad Muneeb Pakistan
Erick Giovani Sperandio Nascimento Brazil
Ahmed M. Elshewey Egypt
Choujun Zhan China
Jyotir Moy Chatterjee India
Ibrahim Gad relative to Abdelkader Dairi Algeria Abdelkader Dairi's profile →
Citations per field
00.5×2.5×
Abdelkader Dairi · 1×
Citations per year

Countries citing papers authored by Ibrahim Gad

Since Specialization
Citations

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

Fields of papers citing papers by Ibrahim Gad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020200
2 2020161
3 202090
4 201271
5 202366
6 202159
7 202054
8 202150
9 202043
10 202240
11 202437
12 202331
13 202030
14 202427
15 201726
16 202022
17 202020
18 202217
19 202316
20 202415

About Ibrahim Gad

Ibrahim Gad is a scholar working on Artificial Intelligence, Computer Networks and Communications, Environmental Engineering, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 1.2k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (8 papers), Network Security and Intrusion Detection (6 papers), COVID-19 epidemiological studies (5 papers), Energy Load and Power Forecasting (5 papers), Wind and Air Flow Studies (4 papers), COVID-19 diagnosis using AI (4 papers), Air Quality and Health Impacts (3 papers) and Air Quality Monitoring and Forecasting (3 papers). The work is most often cited by research in Modeling and Simulation (162 citations), Environmental Engineering (273 citations), Health Information Management (76 citations), Health Informatics (16 citations) and Health, Toxicology and Mutagenesis (160 citations). Ibrahim Gad has collaborated with scholars based in Egypt, Saudi Arabia and India. Frequent co-authors include Doreswamy, El‐Sayed Atlam, Guesh Dagnew, Zohair Malki, El-Sayed Atlam, Ashraf A. Ewis, Aboul Ella Hassanien, Mostafa A. Elhosseini, Osama A. Ghoneim and Amer Malki. Their work appears in journals such as Alexandria Engineering Journal, Neural Computing and Applications, Electronics, Computing and Pharmaceutics.

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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