Joseph Azar

573 total citations
20 papers, 344 citations indexed

About

Joseph Azar is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Joseph Azar has authored 20 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Networks and Communications, 7 papers in Computer Vision and Pattern Recognition and 6 papers in Artificial Intelligence. Recurrent topics in Joseph Azar's work include Anomaly Detection Techniques and Applications (5 papers), IoT and Edge/Fog Computing (4 papers) and IoT Networks and Protocols (3 papers). Joseph Azar is often cited by papers focused on Anomaly Detection Techniques and Applications (5 papers), IoT and Edge/Fog Computing (4 papers) and IoT Networks and Protocols (3 papers). Joseph Azar collaborates with scholars based in France, Lebanon and United States. Joseph Azar's co-authors include Abdallah Makhoul, Raphaël Couturier, Mahmoud Barhamgi, Jacques Demerjian, Christophe Guyeux, Hassan Noura, Ola Salman, Dominique Ginhac, Jacques Bou Abdo and Julien Bourgeois and has published in prestigious journals such as Sensors, Neurocomputing and Future Generation Computer Systems.

In The Last Decade

Joseph Azar

17 papers receiving 329 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Joseph Azar France	7	162	112	87	68	61	20	344
Bharath Sudharsan Ireland	13	161 1.0×	252 2.3×	96 1.1×	116 1.7×	74 1.2×	39	512
T. Revathi India	11	228 1.4×	96 0.9×	71 0.8×	23 0.3×	33 0.5×	49	382
Devendra Prasad India	15	358 2.2×	105 0.9×	184 2.1×	49 0.7×	20 0.3×	67	592
Rohan Tabish United States	13	259 1.6×	62 0.6×	86 1.0×	106 1.6×	17 0.3×	25	514
Mohammed Al‐Maitah Saudi Arabia	10	142 0.9×	55 0.5×	58 0.7×	21 0.3×	31 0.5×	28	296
Miran Taha Spain	13	320 2.0×	42 0.4×	158 1.8×	146 2.1×	82 1.3×	27	500
T. Manikandan India	8	69 0.4×	75 0.7×	61 0.7×	59 0.9×	16 0.3×	47	265
Kiran Sultan Saudi Arabia	11	109 0.7×	53 0.5×	123 1.4×	52 0.8×	14 0.2×	30	339
Ningjiang Chen China	10	231 1.4×	140 1.3×	46 0.5×	120 1.8×	23 0.4×	59	404
Xiaochen Lai China	6	89 0.5×	66 0.6×	37 0.4×	50 0.7×	15 0.2×	26	268

Countries citing papers authored by Joseph Azar

Since Specialization

Citations

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

Fields of papers citing papers by Joseph Azar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joseph Azar

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

All Works

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20 of 20 papers shown

Azar, Joseph, et al.. (2025). Text Mining and Unsupervised Deep Learning for Intrusion Detection in Smart-Grid Communication Networks. IoT. 6(2). 22–22. 3 indexed citations

Azar, Joseph, et al.. (2025). SZ4IoT: an adaptive lightweight lossy compression algorithm for diverse IoT devices and data types. The Journal of Supercomputing. 81(2). 2 indexed citations

Yaacoub, Jean-Paul A., Hassan Noura, Joseph Azar, Ola Salman, & Khaled Chahine. (2024). Cybersecurity in Smart Renewable Energy Systems. 1534–1540. 6 indexed citations

Azar, Joseph, Hassan Noura, & Raphaël Couturier. (2024). Lightweight Image Crypto-Compression Using Haar Transform and Selective Encryption for Grayscale IoT Images. 2. 969–974. 1 indexed citations

Azar, Joseph, et al.. (2024). Leveraging AI for Enhanced Semantic Interoperability in IoT: Insights from NER Models. 1351–1357. 2 indexed citations

Azar, Joseph, et al.. (2023). Lightweight Feature-based Priority Sampling for Industrial IoT Multivariate Time Series. 1–8.

Azar, Joseph, et al.. (2023). Home Automation System with IoT Stack and ChatGPT for People with Reduced Mobility. 3. 44–49. 1 indexed citations

Azar, Joseph, Jacques Bou Abdo, Jacques Demerjian, et al.. (2023). Cross-Layer Federated Learning for Lightweight IoT Intrusion Detection Systems. Sensors. 23(16). 7038–7038. 18 indexed citations

Azar, Joseph, et al.. (2023). Cross-layer Federated Heterogeneous Ensemble Learning for Lightweight IoT Intrusion Detection System. 1–10. 2 indexed citations

10.

Noura, Hassan, et al.. (2022). A deep learning scheme for efficient multimedia IoT data compression. Ad Hoc Networks. 138. 102998–102998. 8 indexed citations

11.

Azar, Joseph, et al.. (2022). A Review of Research on Industrial Time Series Classification for Machinery based on Deep Learning. 89–94. 4 indexed citations

12.

Noura, Hassan, et al.. (2022). A Deep Learning Scheme for Efficient Multimedia Iot Data Compression. SSRN Electronic Journal.

13.

Azar, Joseph, et al.. (2022). Efficient Lossy Compression for IoT Using SZ and Reconstruction with 1D U-Net. Mobile Networks and Applications. 27(3). 984–996. 14 indexed citations

14.

Azar, Joseph, et al.. (2022). On the performance of data-driven approaches for energy efficiency on WiFi and LoRa-based sensors: an experimental study. 2022 International Wireless Communications and Mobile Computing (IWCMC). 883–888. 2 indexed citations

15.

Noura, Hassan, et al.. (2022). An Efficient and Robust MIoT Communication Solution using a Deep Learning Approach. 2022 International Wireless Communications and Mobile Computing (IWCMC). 366–371.

16.

Azar, Joseph, Abdallah Makhoul, Raphaël Couturier, & Jacques Demerjian. (2021). Deep recurrent neural network-based autoencoder for photoplethysmogram artifacts filtering. Computers & Electrical Engineering. 92. 107065–107065. 25 indexed citations

17.

Azar, Joseph, Abdallah Makhoul, & Raphaël Couturier. (2020). Using DenseNet for IoT multivariate time series classification. 1–6. 3 indexed citations

18.

Azar, Joseph, et al.. (2020). A Wearable LoRa-Based Emergency System for Remote Safety Monitoring. 120–125. 20 indexed citations

19.

Azar, Joseph, Abdallah Makhoul, Raphaël Couturier, & Jacques Demerjian. (2020). Robust IoT time series classification with data compression and deep learning. Neurocomputing. 398. 222–234. 55 indexed citations

20.

Azar, Joseph, Abdallah Makhoul, Mahmoud Barhamgi, & Raphaël Couturier. (2019). An energy efficient IoT data compression approach for edge machine learning. Future Generation Computer Systems. 96. 168–175. 178 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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