Majdi Maabreh

518 total citations
20 papers, 259 citations indexed

About

Majdi Maabreh is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Majdi Maabreh has authored 20 papers receiving a total of 259 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 5 papers in Information Systems. Recurrent topics in Majdi Maabreh's work include Advanced Proteomics Techniques and Applications (4 papers), Network Security and Intrusion Detection (4 papers) and Machine Learning in Bioinformatics (3 papers). Majdi Maabreh is often cited by papers focused on Advanced Proteomics Techniques and Applications (4 papers), Network Security and Intrusion Detection (4 papers) and Machine Learning in Bioinformatics (3 papers). Majdi Maabreh collaborates with scholars based in Jordan, United States and Saudi Arabia. Majdi Maabreh's co-authors include Khalil Khan, Ala Al‐Fuqaha, Kashif Ahmad, Junaid Qadir, Ghassan Almasabha, Omar Darwish, Yahya Tashtoush, Izzat Alsmadi, Ajay Gupta and Belal Alsinglawi and has published in prestigious journals such as Multimedia Tools and Applications, Computer Science Review and Arabian Journal for Science and Engineering.

In The Last Decade

Majdi Maabreh

18 papers receiving 249 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Majdi Maabreh Jordan 7 78 58 51 38 35 20 259
Christian Fernández‐Campusano Chile 8 67 0.9× 59 1.0× 116 2.3× 17 0.4× 19 0.5× 26 277
Sujala D. Shetty United Arab Emirates 10 112 1.4× 90 1.6× 58 1.1× 11 0.3× 15 0.4× 34 275
Patrizia Ribino Italy 8 83 1.1× 62 1.1× 28 0.5× 17 0.4× 14 0.4× 40 252
Yazed Alsaawy Saudi Arabia 10 67 0.9× 80 1.4× 77 1.5× 19 0.5× 25 0.7× 31 278
Mohamed Ridda Laouar Algeria 8 56 0.7× 67 1.2× 49 1.0× 16 0.4× 10 0.3× 48 202
Muhammad Ehsan Rana Malaysia 12 80 1.0× 121 2.1× 88 1.7× 18 0.5× 24 0.7× 106 394
Aritz Bilbao-Jayo Spain 9 52 0.7× 32 0.6× 106 2.1× 111 2.9× 16 0.5× 15 325
Murad Al-Rajab United Arab Emirates 6 67 0.9× 59 1.0× 34 0.7× 13 0.3× 16 0.5× 25 213
Irfan Syamsuddin Indonesia 8 39 0.5× 76 1.3× 45 0.9× 23 0.6× 13 0.4× 42 255
Lamia Karim Morocco 7 39 0.5× 38 0.7× 61 1.2× 26 0.7× 10 0.3× 26 219

Countries citing papers authored by Majdi Maabreh

Since Specialization
Citations

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

Fields of papers citing papers by Majdi Maabreh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Majdi Maabreh

This figure shows the co-authorship network connecting the top 25 collaborators of Majdi Maabreh. A scholar is included among the top collaborators of Majdi Maabreh based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Majdi Maabreh. Majdi Maabreh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tashtoush, Yahya, et al.. (2025). A Deep Learning Framework for Arabic Cyberbullying Detection in Social Networks. Computers, materials & continua/Computers, materials & continua (Print). 83(2). 3113–3134. 1 indexed citations
2.
Maabreh, Majdi, et al.. (2023). Assessing the Impact and Effectiveness of Cybersecurity Measures in e-Learning on Students and Educators: A Case Study. International Journal of Advanced Computer Science and Applications. 14(5). 12 indexed citations
3.
Maabreh, Majdi & Ghassan Almasabha. (2023). Machine Learning Regression Algorithms for Shear Strength Prediction of SFRC-DBs: Performance Evaluation and Comparisons. Arabian Journal for Science and Engineering. 49(4). 4711–4727. 24 indexed citations
4.
Darwish, Omar, et al.. (2023). A deep learning approach for detecting covert timing channel attacks using sequential data. Cluster Computing. 27(2). 1655–1665. 6 indexed citations
5.
Alsadoon, Abeer, Ghazi Al‐Naymat, Ahmed Hamza Osman, et al.. (2023). DFCV: a framework for evaluation deep learning in early detection and classification of lung cancer. Multimedia Tools and Applications. 82(28). 44387–44430. 8 indexed citations
6.
Tashtoush, Yahya, et al.. (2022). Survey on authentication and security protocols and schemes over 5G networks. International Journal of Distributed Sensor Networks. 18(10). 3627531330–3627531330. 4 indexed citations
7.
Maabreh, Majdi, et al.. (2022). The robustness of popular multiclass machine learning models against poisoning attacks: Lessons and insights. International Journal of Distributed Sensor Networks. 18(7). 3627531115–3627531115. 3 indexed citations
8.
Darwish, Omar, et al.. (2022). A Classifier to Detect Stream Applications Based on Network Traffic Statistical Metrics. 35. 1–8. 1 indexed citations
9.
Maabreh, Majdi, et al.. (2022). Towards Data-Driven Network Intrusion Detection Systems: Features Dimensionality Reduction and Machine Learning. International Journal of Interactive Mobile Technologies (iJIM). 16(14). 123–135. 11 indexed citations
10.
11.
Tashtoush, Yahya, et al.. (2022). A Deep Learning Framework for Detection of COVID-19 Fake News on Social Media Platforms. Data. 7(5). 65–65. 29 indexed citations
12.
Ahmad, Kashif, et al.. (2021). Developing future human-centered smart cities: Critical analysis of smart city security, Data management, and Ethical challenges. Computer Science Review. 43. 100452–100452. 136 indexed citations
13.
Tashtoush, Yahya, et al.. (2021). Enhancing Robots Navigation in Internet of Things Indoor Systems. Computers. 10(11). 153–153. 2 indexed citations
14.
Maabreh, Majdi, et al.. (2017). A multithreading and hashing technique for indexing Target‐Decoy peptides databases. Concurrency and Computation Practice and Experience. 30(9). 1 indexed citations
15.
16.
Maabreh, Majdi, Basheer Qolomany, Ajay Gupta, & James R. Springstead. (2017). Optimizing Protein Search Engines using Particle Swarm Optimization. 340–345. 1 indexed citations
17.
Maabreh, Majdi, Ajay Gupta, & Fahad Saeed. (2016). A parallel peptide indexer and decoy generator for crux tide using OpenMP. 411–418. 3 indexed citations
18.
Maabreh, Majdi & Izzat Alsmadi. (2015). A Survey of Impact and Citation Indices: Limitations and Issues. 11 indexed citations
19.
Al‐Kabi, Mohammed N., et al.. (2014). Studying and analysing students web search behaviours within three Jordanian universities. International Journal of Continuing Engineering Education and Life-Long Learning. 24(3/4). 388–388.
20.
Maabreh, Majdi, Mohammed N. Al‐Kabi, & Izzat Alsmadi. (2012). Query classification and study of university students' search trends. Program electronic library and information systems. 46(2). 220–241. 3 indexed citations

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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