Shavan Askar

1.2k total citations
97 papers, 760 citations indexed

About

Shavan Askar is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Information Systems. According to data from OpenAlex, Shavan Askar has authored 97 papers receiving a total of 760 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Computer Networks and Communications, 30 papers in Electrical and Electronic Engineering and 18 papers in Information Systems. Recurrent topics in Shavan Askar's work include IoT and Edge/Fog Computing (24 papers), Network Security and Intrusion Detection (11 papers) and Software-Defined Networks and 5G (9 papers). Shavan Askar is often cited by papers focused on IoT and Edge/Fog Computing (24 papers), Network Security and Intrusion Detection (11 papers) and Software-Defined Networks and 5G (9 papers). Shavan Askar collaborates with scholars based in Iraq, India and Saudi Arabia. Shavan Askar's co-authors include Shahab Wahhab Kareem, Subhi R. M. Zeebaree, Kayhan Zrar Ghafoor, Ahmed Alawadi, Adnan Mohsin Abdulazeez, Arif Sarı, Iskandar Muda, Tarik A. Rashid, Natalia Prodanova and Ebraheem Abdu Musad Saleh and has published in prestigious journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and Chemosphere.

In The Last Decade

Shavan Askar

82 papers receiving 722 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shavan Askar Iraq 17 351 177 150 109 63 97 760
Haydar Abdulameer Marhoon Iraq 16 171 0.5× 127 0.7× 107 0.7× 107 1.0× 70 1.1× 58 682
V. Parthasarathy India 19 224 0.6× 468 2.6× 104 0.7× 93 0.9× 118 1.9× 106 1.1k
Abdelbaki El Belrhiti El Alaoui Morocco 13 477 1.4× 228 1.3× 70 0.5× 102 0.9× 56 0.9× 37 687
Jiaxin Du China 17 369 1.1× 203 1.1× 64 0.4× 66 0.6× 92 1.5× 33 766
Dalia H. Elkamchouchi Saudi Arabia 16 107 0.3× 367 2.1× 63 0.4× 112 1.0× 124 2.0× 58 788
Rajesh Sankaran United States 11 719 2.0× 226 1.3× 245 1.6× 138 1.3× 80 1.3× 31 1.1k
Mohammed Assiri Saudi Arabia 12 85 0.2× 140 0.8× 46 0.3× 94 0.9× 35 0.6× 67 465
Mongkol Ekpanyapong Thailand 17 175 0.5× 270 1.5× 47 0.3× 98 0.9× 205 3.3× 81 939
Zhe Sun China 17 250 0.7× 378 2.1× 57 0.4× 281 2.6× 40 0.6× 61 1.1k
R. Maheswar India 17 385 1.1× 477 2.7× 57 0.4× 62 0.6× 35 0.6× 88 941

Countries citing papers authored by Shavan Askar

Since Specialization
Citations

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

Fields of papers citing papers by Shavan Askar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shavan Askar

This figure shows the co-authorship network connecting the top 25 collaborators of Shavan Askar. A scholar is included among the top collaborators of Shavan Askar 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 Shavan Askar. Shavan Askar 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.
Askar, Shavan, et al.. (2025). Integration of Deep Learning Applications and IoT for Smart Healthcare. Indonesian Journal of Computer Science. 14(1). 1 indexed citations
2.
Mahmood, Nasrul Humaimi, et al.. (2025). Machine Learning for Network Anomaly Detection A Review. Indonesian Journal of Computer Science. 14(1).
3.
Askar, Shavan, et al.. (2025). Deep Learning Techniques for Network Security. Indonesian Journal of Computer Science. 14(1).
4.
Ahmed, Zuhair, et al.. (2025). Fog Computing Challenges and Opportunities in IoT Networks: A Review. Procedia Computer Science. 259. 1749–1764.
5.
Sarı, Arif, et al.. (2025). Machine Learning-Aided Examination of Energy Absorption and Mechanical Properties in Steel Lattice Structures. Transactions of the Indian Institute of Metals. 78(3). 1 indexed citations
6.
Sharma, M. K., et al.. (2024). FEM-supported machine learning for residual stress and cutting force analysis in micro end milling of aluminum alloys. International Journal of Mechanics and Materials in Design. 20(5). 1077–1098. 5 indexed citations
7.
Askar, Shavan, et al.. (2024). Exploring the Landscape of Smart Cities: A Comprehensive Review of IoT and Cyber-Physical Systems. Indonesian Journal of Computer Science. 13(2). 1 indexed citations
8.
Mansouri, Sofiène, et al.. (2024). An artificial intelligence approach to predict infants’ health status at birth. International Journal of Medical Informatics. 183. 105338–105338. 5 indexed citations
9.
Shukur, Hanan M., Shavan Askar, & Subhi R. M. Zeebaree. (2024). THE UTILIZATION OF 6G IN INDUSTRY 4.0. Applied Computer Science. 20(2). 75–89. 1 indexed citations
10.
AlZohbi, Gaydaa, et al.. (2024). Sustainable building materials for Eco-friendly construction. AIP conference proceedings. 3217. 40005–40005.
11.
Pallathadka, Harikumar, et al.. (2023). Probing the impact of process variables in laser-welded aluminum alloys: A machine learning study. Materials Today Communications. 38. 107660–107660. 9 indexed citations
12.
Candra, Oriza, Amjad Ali, Shavan Askar, et al.. (2023). Thermal and environmental optimization of an intercooled gas turbine toward a sustainable environment. Chemosphere. 339. 139624–139624. 2 indexed citations
13.
Askar, Shavan, et al.. (2023). A micromechanical nested machine learning model for characterizing materials behaviors of bulk metallic glasses. Journal of Non-Crystalline Solids. 625. 122733–122733. 7 indexed citations
14.
Al‐Hawary, Sulieman Ibraheem Shelash, et al.. (2023). Recent advances in nanomaterials-based electrochemical and optical sensing approaches for detection of food dyes in food samples: A comprehensive overview. Microchemical Journal. 189. 108540–108540. 25 indexed citations
15.
Rashid, Tarik A., et al.. (2023). CDDO–HS: Child Drawing Development Optimization–Harmony Search Algorithm. Applied Sciences. 13(9). 5795–5795. 7 indexed citations
16.
Alawadi, Ahmed, et al.. (2023). Assessment of Nano-Imprinting Process in CuZr Amorphous Films Through Combination of Machine Learning and Molecular Dynamics. Journal of Electronic Materials. 52(10). 6943–6958. 3 indexed citations
17.
Askar, Shavan. (2023). Deep Forest Based Internet of Medical Things System for Diagnosis of Heart Disease. SHILAP Revista de lepidopterología. 11(1). 88–98. 6 indexed citations
18.
Askar, Shavan, et al.. (2022). Flood Susceptibility Mapping Using Remote Sensing and Integration of Decision Table Classifier and Metaheuristic Algorithms. Water. 14(19). 3062–3062. 41 indexed citations
19.
Askar, Shavan. (2017). SDN-Based Load Balancing Scheme for Fat-Tree Data Center Networks. SHILAP Revista de lepidopterología. 20(5). 1047–1056. 5 indexed citations
20.
Askar, Shavan, Georgios Zervas, David K. Hunter, & Dimitra Simeonidou. (2011). Service differentiation for video applications over OBS networks. UCL Discovery (University College London). 200–203.

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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