Hadjar Ould Slimane

492 total citations · 1 hit paper
7 papers, 254 citations indexed

About

Hadjar Ould Slimane is a scholar working on Aerospace Engineering, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Hadjar Ould Slimane has authored 7 papers receiving a total of 254 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Aerospace Engineering, 4 papers in Electrical and Electronic Engineering and 3 papers in Artificial Intelligence. Recurrent topics in Hadjar Ould Slimane's work include Vehicular Ad Hoc Networks (VANETs) (3 papers), Adversarial Robustness in Machine Learning (2 papers) and Smart Grid Security and Resilience (2 papers). Hadjar Ould Slimane is often cited by papers focused on Vehicular Ad Hoc Networks (VANETs) (3 papers), Adversarial Robustness in Machine Learning (2 papers) and Smart Grid Security and Resilience (2 papers). Hadjar Ould Slimane collaborates with scholars based in United States. Hadjar Ould Slimane's co-authors include Naima Kaabouch, Tala Talaei Khoei, Khair Al Shamaileh, V. Devabhaktuni and Vijay Devabhaktuni and has published in prestigious journals such as Neural Computing and Applications and Communications and Network.

In The Last Decade

Hadjar Ould Slimane

7 papers receiving 242 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep learning: systematic review, models, challenges, and research directions

2023 163 citations Tala Talaei Khoei, Hadjar Ould Slimane et al. Neural Computing and Applications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hadjar Ould Slimane United States	5	87	50	48	45	34	7	254
Haonan Guo China	8	45 0.5×	48 1.0×	42 0.9×	27 0.6×	22 0.6×	32	231
Shuai Sun China	10	54 0.6×	95 1.9×	63 1.3×	31 0.7×	53 1.6×	38	231
Xiaoliang Feng China	8	86 1.0×	56 1.1×	59 1.2×	94 2.1×	33 1.0×	47	288
Lahiru Jayasinghe Singapore	7	66 0.8×	95 1.9×	25 0.5×	62 1.4×	87 2.6×	11	286
Gholamreza Farahani Iran	10	115 1.3×	151 3.0×	70 1.5×	59 1.3×	20 0.6×	37	337
Dejun Mu China	11	105 1.2×	96 1.9×	122 2.5×	98 2.2×	85 2.5×	51	347
Ze Zhang China	9	37 0.4×	33 0.7×	33 0.7×	24 0.5×	21 0.6×	46	250
Phaklen Ehkan Malaysia	9	57 0.7×	134 2.7×	85 1.8×	14 0.3×	20 0.6×	58	298
Maciej Nikodem Poland	10	47 0.5×	138 2.8×	88 1.8×	16 0.4×	37 1.1×	37	281
Xiaojia Han China	10	86 1.0×	103 2.1×	81 1.7×	179 4.0×	26 0.8×	19	311

Countries citing papers authored by Hadjar Ould Slimane

Since Specialization

Citations

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

Fields of papers citing papers by Hadjar Ould Slimane

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hadjar Ould Slimane. 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 Hadjar Ould Slimane. The network helps show where Hadjar Ould Slimane may publish in the future.

Co-authorship network of co-authors of Hadjar Ould Slimane

This figure shows the co-authorship network connecting the top 25 collaborators of Hadjar Ould Slimane. A scholar is included among the top collaborators of Hadjar Ould Slimane 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 Hadjar Ould Slimane. Hadjar Ould Slimane is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Khoei, Tala Talaei, Hadjar Ould Slimane, Khair Al Shamaileh, V. Devabhaktuni, & Naima Kaabouch. (2024). Detecting Injection Attacks in ADS-B Devices Using RNN-Based Models. 1–8. 1 indexed citations

2.

Slimane, Hadjar Ould, et al.. (2023). A Machine Learning Approach for the Detection of Injection Attacks on ADS-B Messaging Systems. 293–297. 1 indexed citations

3.

Khoei, Tala Talaei, Hadjar Ould Slimane, & Naima Kaabouch. (2023). Deep learning: systematic review, models, challenges, and research directions. Neural Computing and Applications. 35(31). 23103–23124. 163 indexed citations breakdown →

4.

Slimane, Hadjar Ould, et al.. (2022). A Light Boosting-based ML Model for Detecting Deceptive Jamming Attacks on UAVs. 328–333. 8 indexed citations

5.

Slimane, Hadjar Ould, et al.. (2022). ADS-B Message Injection Attack on UAVs: Assessment of SVM-based Detection Techniques. 405–410. 9 indexed citations

6.

Khoei, Tala Talaei, Hadjar Ould Slimane, & Naima Kaabouch. (2022). Cyber-Security of Smart Grids: Attacks, Detection, Countermeasure Techniques, and Future Directions. Communications and Network. 14(4). 119–170. 32 indexed citations

7.

Slimane, Hadjar Ould, et al.. (2021). Tree-based Supervised Machine Learning Models For Detecting GPS Spoofing Attacks on UAS. 649–653. 40 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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