Mohammed R. Saad

756 total citations · 1 hit paper
10 papers, 564 citations indexed

About

Mohammed R. Saad is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computational Theory and Mathematics. According to data from OpenAlex, Mohammed R. Saad has authored 10 papers receiving a total of 564 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Computer Networks and Communications and 5 papers in Computational Theory and Mathematics. Recurrent topics in Mohammed R. Saad's work include Metaheuristic Optimization Algorithms Research (8 papers), Advanced Multi-Objective Optimization Algorithms (5 papers) and Energy Efficient Wireless Sensor Networks (3 papers). Mohammed R. Saad is often cited by papers focused on Metaheuristic Optimization Algorithms Research (8 papers), Advanced Multi-Objective Optimization Algorithms (5 papers) and Energy Efficient Wireless Sensor Networks (3 papers). Mohammed R. Saad collaborates with scholars based in Egypt, China and Norway. Mohammed R. Saad's co-authors include Essam H. Houssein, Hassan Shaban, M. Hassaballah, Fatma A. Hashim, Kashif Hussain, William Zhu, Abdelmgeid A. Ali, Marwa M. Emam, Youcef Djenouri and Mosa E. Hosney and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Mohammed R. Saad

10 papers receiving 550 citations

Hit Papers

Lévy flight distribution: A new metaheuristic algorithm f... 2020 2026 2022 2024 2020 100 200 300

Peers

Mohammed R. Saad
Mohammed R. Saad
Citations per year, relative to Mohammed R. Saad Mohammed R. Saad (= 1×) peers Ahmed F. Ali

Countries citing papers authored by Mohammed R. Saad

Since Specialization
Citations

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

Fields of papers citing papers by Mohammed R. Saad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammed R. Saad. 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 Mohammed R. Saad. The network helps show where Mohammed R. Saad may publish in the future.

Co-authorship network of co-authors of Mohammed R. Saad

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

All Works

10 of 10 papers shown
1.
Emam, Marwa M., Mohammed R. Saad, Mina Younan, & Essam H. Houssein. (2025). An efficient enhanced exponential distribution optimizer: applications in global, engineering, and combinatorial optimization problems. Journal Of Big Data. 12(1). 3 indexed citations
2.
Saad, Mohammed R., Marwa M. Emam, & Essam H. Houssein. (2025). An efficient multi-objective parrot optimizer for global and engineering optimization problems. Scientific Reports. 15(1). 5126–5126. 4 indexed citations
3.
Hosney, Mosa E., Essam H. Houssein, Mohammed R. Saad, et al.. (2024). Efficient bladder cancer diagnosis using an improved RIME algorithm with Orthogonal Learning. Computers in Biology and Medicine. 182. 109175–109175. 9 indexed citations
4.
Houssein, Essam H., et al.. (2024). Metaheuristic algorithms and their applications in wireless sensor networks: review, open issues, and challenges. Cluster Computing. 27(10). 13643–13673. 17 indexed citations
5.
Houssein, Essam H., Mohammed R. Saad, Emre Çelik, et al.. (2024). An enhanced sea-horse optimizer for solving global problems and cluster head selection in wireless sensor networks. Cluster Computing. 27(6). 7775–7802. 7 indexed citations
6.
Houssein, Essam H., Mohammed R. Saad, Abdelmgeid A. Ali, & Hassan Shaban. (2023). Multiple Strategies Boosted Orca Predation Algorithm for Engineering Optimization Problems. International Journal of Computational Intelligence Systems. 16(1). 3 indexed citations
7.
Houssein, Essam H., Mohammed R. Saad, Abdelmgeid A. Ali, & Hassan Shaban. (2022). An efficient multi-objective gorilla troops optimizer for minimizing energy consumption of large-scale wireless sensor networks. Expert Systems with Applications. 212. 118827–118827. 34 indexed citations
8.
Houssein, Essam H., Mohammed R. Saad, Kashif Hussain, Hassan Shaban, & M. Hassaballah. (2021). A Review of Metaheuristic Optimization Algorithms in Wireless Sensor Networks. Studies in computational intelligence. 193–217. 5 indexed citations
9.
Houssein, Essam H., Mohammed R. Saad, Kashif Hussain, et al.. (2020). Optimal Sink Node Placement in Large Scale Wireless Sensor Networks Based on Harris’ Hawk Optimization Algorithm. IEEE Access. 8. 19381–19397. 101 indexed citations
10.
Houssein, Essam H., Mohammed R. Saad, Fatma A. Hashim, Hassan Shaban, & M. Hassaballah. (2020). Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems. Engineering Applications of Artificial Intelligence. 94. 103731–103731. 381 indexed citations breakdown →

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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