Adil Bagirov

4.1k total citations
134 papers, 2.5k citations indexed

About

Adil Bagirov is a scholar working on Artificial Intelligence, Numerical Analysis and Computational Theory and Mathematics. According to data from OpenAlex, Adil Bagirov has authored 134 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 39 papers in Numerical Analysis and 36 papers in Computational Theory and Mathematics. Recurrent topics in Adil Bagirov's work include Advanced Optimization Algorithms Research (39 papers), Face and Expression Recognition (27 papers) and Advanced Clustering Algorithms Research (26 papers). Adil Bagirov is often cited by papers focused on Advanced Optimization Algorithms Research (39 papers), Face and Expression Recognition (27 papers) and Advanced Clustering Algorithms Research (26 papers). Adil Bagirov collaborates with scholars based in Australia, Finland and Türkiye. Adil Bagirov's co-authors include Napsu Karmitsa, Julien Ugon, John Yearwood, Marko M. Mäkelä, A. M. Rubinov, Sona Taheri, Nargiz Sultanova, Andrew Barton, Dean Webb and Ramiz M. Aliguliyev and has published in prestigious journals such as SHILAP Revista de lepidopterología, Bioinformatics and IEEE Transactions on Information Theory.

In The Last Decade

Adil Bagirov

121 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Adil Bagirov Australia 28 875 726 669 468 423 134 2.5k
Jing Zhao China 20 848 1.0× 383 0.5× 238 0.4× 593 1.3× 108 0.3× 128 2.5k
Katta G. Murty United States 25 547 0.6× 1.1k 1.5× 818 1.2× 233 0.5× 214 0.5× 78 4.3k
Guanghui Lan United States 28 2.5k 2.8× 654 0.9× 852 1.3× 309 0.7× 2.0k 4.7× 78 4.0k
Jian Yu China 28 761 0.9× 633 0.9× 131 0.2× 917 2.0× 166 0.4× 181 3.4k
J. B. Rosen United States 27 427 0.5× 1.4k 1.9× 1.4k 2.1× 394 0.8× 416 1.0× 92 3.5k
Jon Lee United States 26 453 0.5× 1.0k 1.4× 706 1.1× 146 0.3× 370 0.9× 172 3.8k
Taiyong Li China 30 513 0.6× 450 0.6× 150 0.2× 519 1.1× 201 0.5× 92 2.3k
Marko M. Mäkelä Finland 21 375 0.4× 1.2k 1.6× 697 1.0× 123 0.3× 372 0.9× 76 1.9k
Mehrdad Mahdavi United States 19 1.9k 2.2× 888 1.2× 83 0.1× 501 1.1× 240 0.6× 49 3.4k
Xiangmin Zhou Australia 24 418 0.5× 74 0.1× 633 0.9× 351 0.8× 436 1.0× 114 2.1k

Countries citing papers authored by Adil Bagirov

Since Specialization
Citations

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

Fields of papers citing papers by Adil Bagirov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adil Bagirov

This figure shows the co-authorship network connecting the top 25 collaborators of Adil Bagirov. A scholar is included among the top collaborators of Adil Bagirov 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 Adil Bagirov. Adil Bagirov 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.
Bagirov, Adil, Napsu Karmitsa, & Sona Taheri. (2024). Partitional Clustering via Nonsmooth Optimization.
2.
Karmitsa, Napsu, et al.. (2023). Nonsmooth Optimization-Based Hyperparameter-Free Neural Networks for Large-Scale Regression. Algorithms. 16(9). 444–444.
3.
Barton, Andrew, et al.. (2021). Analysis of Water Quantity and Quality Trade-Offs to Inform Selective Harvesting of Inflows in Complex Water Resource Systems. Water Resources Management. 35(12). 4149–4165. 2 indexed citations
4.
Gondal, Iqbal, et al.. (2021). Malware Variant Identification Using Incremental Clustering. Electronics. 10(14). 1628–1628. 6 indexed citations
5.
Estrada‐Moreno, Alejandro, et al.. (2019). A biased-randomised algorithm for the capacitated facility location problem with soft constraints. Journal of the Operational Research Society. 71(11). 1799–1815. 11 indexed citations
6.
Bagirov, Adil, et al.. (2019). A difference of convex optimization algorithm for piecewise linear regression. Journal of Industrial and Management Optimization. 15(2). 909–932. 3 indexed citations
7.
Bagirov, Adil, Gürkan Öztürk, & Refail Kasımbeyli. (2018). A sharp augmented Lagrangian-based method in constrained non-convex optimization. Optimization methods & software. 34(3). 462–488. 7 indexed citations
8.
Gaudioso, Manlio, Giovanni Giallombardo, Giovanna Miglionico, & Adil Bagirov. (2017). Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations. Journal of Global Optimization. 71(1). 37–55. 41 indexed citations
9.
Bagirov, Adil. (2015). CONTINUOUS SUBDIFFERENTIAL APPROXIMATION AND ITS CONSTRUCTION. SHILAP Revista de lepidopterología.
10.
Bagirov, Adil, et al.. (2012). A novel approach to optimal pump scheduling in water distribution systems. FedUni ResearchOnline (Federation University Australia). 618–631. 2 indexed citations
11.
Bagirov, Adil, et al.. (2012). Application of Optimisation-Based Data Mining Techniques to Medical Data Sets: A Comparative Analysis. FedUni ResearchOnline (Federation University Australia). 41–46. 1 indexed citations
12.
Bagirov, Adil, et al.. (2012). Comparison of metaheuristic algorithms for pump operation optimization. FedUni ResearchOnline (Federation University Australia). 886. 3 indexed citations
13.
Bagirov, Adil, et al.. (2012). Minimization of pumping costs in water distribution systems using explicit and implicit pump scheduling. 1298. 1 indexed citations
14.
Taheri, Sona, Musa Mammadov, & Adil Bagirov. (2011). Improving naive Bayes classifier using conditional probabilities. FedUni ResearchOnline (Federation University Australia). 63–68. 18 indexed citations
15.
Bagirov, Adil, et al.. (2010). Cluster analysis of a tobacco control data set. FedUni ResearchOnline (Federation University Australia). 1 indexed citations
16.
Bagirov, Adil, et al.. (2010). A generalized subgradient method with piecewise linear subproblem. FedUni ResearchOnline (Federation University Australia). 17(5). 621–638. 2 indexed citations
17.
Bagirov, Adil, Julien Ugon, & Dean Webb. (2009). A new modified global k-means algorithm for clustering large data sets. FedUni ResearchOnline (Federation University Australia). 2 indexed citations
18.
Mason, Thomas L., et al.. (2007). Integrated production system optimization using global optimization techniques. Journal of Industrial and Management Optimization. 3(2). 257–277. 9 indexed citations
19.
Bagirov, Adil, et al.. (2003). Optimization based clustering algorithms in Multicast group Hierarchies. FedUni ResearchOnline (Federation University Australia).
20.
Bagirov, Adil, et al.. (1992). A method of approximating a quasidifferential. Computational Mathematics and Mathematical Physics. 35(4). 403–409. 14 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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