Ali Shakiba

29 papers receiving 357 citations

Peers

Ali Shakiba
Comparison fields: 5 of 54
  • Computer Vision and Pattern Recognition 116
  • Modeling and Simulation 112
  • Computational Theory and Mathematics 84
  • Artificial Intelligence 73
  • Numerical Analysis 58
Replace Samy Wu Fung with:
Samy Wu Fung United States
Bin Pei China
G. Arthi South Korea
Ali F. Jameel Malaysia
Maulana Malik Indonesia
Jean Vignes France
S. Raja Balachandar India
Ebru Ozbılge Türkiye
Qinghua Ma China
Shiguo Peng China
Ali Shakiba relative to Samy Wu Fung United States Samy Wu Fung's profile →
Citations per field
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Citations per year

Countries citing papers authored by Ali Shakiba

Since Specialization
Citations

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

Fields of papers citing papers by Ali Shakiba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Shakiba

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Shakiba. A scholar is included among the top collaborators of Ali Shakiba 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 Ali Shakiba. Ali Shakiba 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
#WorkIndexed citations
1 1
2 0
3 0
4 10
5 27
6 6
7 4
8 3
9 31
10 8
11
On the complexity of the outer-connected bondage and the outer-connected reinforcement problems
1
12 3
13 4
14 9
15 7
16 41
17 16
18
Sedimentary and Environmental Geochemistry of metals in the surface Sediments of the North-west of Persian Gulf (Boushehr Province Area)
1
19 11
20 12

About Ali Shakiba

Ali Shakiba is a scholar working on Computational Theory and Mathematics, Modeling and Simulation and Discrete Mathematics and Combinatorics, having authored 32 papers that have together received 369 indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (9 papers), Rough Sets and Fuzzy Logic (7 papers) and Cryptographic Implementations and Security (6 papers). The work is most often cited by research in Modeling and Simulation (112 citations), Numerical Analysis (58 citations) and Computer Vision and Pattern Recognition (116 citations). Ali Shakiba has collaborated with scholars based in Iran, Australia and Italy. Frequent co-authors include M. R. Hooshmandasl, Mohammad Heydari, Z. Avazzadeh, Mohammad Reza Mahmoudi, Carlo Cattani, Amir Kafshdar Goharshady, Mohammad Alipour, Praveennath G. Koppad, R. Keshavamurthy and Bijan Davvaz. Their work appears in journals such as Nonlinear Dynamics, Communications in Nonlinear Science and Numerical Simulation and International Journal of Bifurcation and Chaos.

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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