Monir Abdullah

460 total citations
44 papers, 245 citations indexed

About

Monir Abdullah is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Monir Abdullah has authored 44 papers receiving a total of 245 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Networks and Communications, 18 papers in Artificial Intelligence and 16 papers in Information Systems. Recurrent topics in Monir Abdullah's work include Cloud Computing and Resource Management (11 papers), Network Security and Intrusion Detection (8 papers) and Distributed and Parallel Computing Systems (8 papers). Monir Abdullah is often cited by papers focused on Cloud Computing and Resource Management (11 papers), Network Security and Intrusion Detection (8 papers) and Distributed and Parallel Computing Systems (8 papers). Monir Abdullah collaborates with scholars based in Saudi Arabia, Malaysia and Yemen. Monir Abdullah's co-authors include Мohamed Othman, Ramin Yahyapour, Philipp Wieder, Hamidah Ibrahim, Constantinos Kotsokalis, Mohammad Tabrez Quasim, Shamala Subramaniam, Sohaib Asif, Surendra P. Singh and Mohammad Ayoub Khan and has published in prestigious journals such as Scientific Reports, IEEE Access and BMC Bioinformatics.

In The Last Decade

Monir Abdullah

32 papers receiving 218 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Monir Abdullah Saudi Arabia 9 150 128 43 25 22 44 245
Mehboob Hussain China 8 159 1.1× 158 1.2× 49 1.1× 21 0.8× 15 0.7× 17 263
Wu Zhang China 8 129 0.9× 148 1.2× 50 1.2× 15 0.6× 20 0.9× 21 275
G. Kavitha India 7 169 1.1× 157 1.2× 36 0.8× 25 1.0× 6 0.3× 42 250
Rajender Singh Chhillar India 12 95 0.6× 151 1.2× 69 1.6× 19 0.8× 9 0.4× 46 302
Christos Kloukinas United Kingdom 10 96 0.6× 92 0.7× 102 2.4× 18 0.7× 34 1.5× 31 289
Houshyar Honar Pajooh New Zealand 6 195 1.3× 242 1.9× 58 1.3× 42 1.7× 7 0.3× 6 304
Debabrata Sarddar India 8 153 1.0× 114 0.9× 39 0.9× 42 1.7× 8 0.4× 53 222
Jinnan Guo China 4 121 0.8× 214 1.7× 87 2.0× 32 1.3× 12 0.5× 6 268
Ahsan Ali United States 9 169 1.1× 132 1.0× 76 1.8× 18 0.7× 6 0.3× 28 292
Mangayarkarasi Ramaiah India 9 118 0.8× 88 0.7× 103 2.4× 12 0.5× 15 0.7× 32 231

Countries citing papers authored by Monir Abdullah

Since Specialization
Citations

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

Fields of papers citing papers by Monir Abdullah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Monir Abdullah

This figure shows the co-authorship network connecting the top 25 collaborators of Monir Abdullah. A scholar is included among the top collaborators of Monir Abdullah 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 Monir Abdullah. Monir Abdullah 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.
Zou, Beiji, et al.. (2025). A Novel CAPTCHA Recognition System Based on Refined Visual Attention. Computers, materials & continua/Computers, materials & continua (Print). 83(1). 115–136.
2.
Abdullah, Monir, et al.. (2025). Hybrid deep learning models with spotted hyena optimization for cloud computing enabled intrusion detection system. Journal of Radiation Research and Applied Sciences. 18(2). 101523–101523.
3.
Abdullah, Monir, et al.. (2025). Federated learning with Blockchain on Denial-of-Service attacks detection and classification of edge IIoT networks using Deep Transfer Learning model. Computers & Electrical Engineering. 124. 110319–110319. 1 indexed citations
4.
Zhu, Chengzhang, et al.. (2025). AMSFuse: Adaptive Multi-Scale Feature Fusion Network for Diabetic Retinopathy Classification. Computers, materials & continua/Computers, materials & continua (Print). 82(3). 5153–5167. 5 indexed citations
5.
6.
Alghamdi, Mohammed Hussien, et al.. (2025). Computer vision assisted deep transfer learning model for accurate grading of renal cell carcinoma from kidney histopathology images. Scientific Reports. 15(1). 36005–36005.
7.
Alamgeer, Mohammad, et al.. (2025). Design of advanced intrusion detection in cybersecurity using ensemble of deep learning models with an improved beluga whale optimization algorithm. Alexandria Engineering Journal. 121. 90–102. 3 indexed citations
8.
Xing, Huanlai, et al.. (2025). MGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction. BMC Bioinformatics. 26(1). 19–19. 1 indexed citations
9.
Fiaz, Muhammad, Muhammad Bilal Khan, Abdul Hannan Khan, et al.. (2025). An explainable hybrid deep learning framework for precise skin lesion segmentation and multi-class classification. Frontiers in Medicine. 12. 1681542–1681542.
10.
Abdullah, Monir. (2025). Artificial intelligence-based framework for early detection of heart disease using enhanced multilayer perceptron. Frontiers in Artificial Intelligence. 7. 1539588–1539588. 2 indexed citations
11.
12.
Asif, Sohaib, et al.. (2024). LitefusionNet: Boosting the performance for medical image classification with an intelligent and lightweight feature fusion network. Journal of Computational Science. 80. 102324–102324. 7 indexed citations
13.
Abdullah, Monir, et al.. (2024). Shapley-guided pruning for efficient graph neural architecture prediction in distributed learning environments. Information Sciences. 695. 121695–121695. 1 indexed citations
14.
Maray, Mohammed, et al.. (2024). Mathematical modelling-based blockchain with attention deep learning model for cybersecurity in IoT-consumer electronics. Alexandria Engineering Journal. 113. 366–377. 2 indexed citations
15.
Abdullah, Monir, et al.. (2024). DDoS Attacks Detection in IoV using ML-based Models with an Enhanced Feature Selection Technique. International Journal of Advanced Computer Science and Applications. 15(2). 2 indexed citations
16.
Abdullah, Monir, et al.. (2024). A Taxonomy of IDS in IoTs: ML Classifiers, Feature Selection Models, Datasets and Future Directions. International Journal of Advanced Computer Science and Applications. 15(6).
17.
Abdullah, Monir, et al.. (2024). Improving the Performance of Bully Algorithm for Leader Election in Distributed Systems. 1–7. 1 indexed citations
18.
19.
Quasim, Mohammad Tabrez, et al.. (2023). An internet of things enabled machine learning model for Energy Theft Prevention System (ETPS) in Smart Cities. Journal of Cloud Computing Advances Systems and Applications. 12(1). 10 indexed citations
20.
Abdullah, Monir & Мohamed Othman. (2015). Scheduling divisible jobs to optimize the computation and energy costs. 2 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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