Mohammad Al-Rubaie

About

Mohammad Al-Rubaie is a scholar working on Artificial Intelligence, Sociology and Political Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mohammad Al-Rubaie has authored 3 papers receiving a total of 216 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Sociology and Political Science and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Mohammad Al-Rubaie’s work include Cryptography and Data Security (2 papers), Privacy-Preserving Technologies in Data (2 papers) and Adversarial Robustness in Machine Learning (1 paper). Mohammad Al-Rubaie is often cited by papers focused on Cryptography and Data Security (2 papers), Privacy-Preserving Technologies in Data (2 papers) and Adversarial Robustness in Machine Learning (1 paper). Mohammad Al-Rubaie collaborates with scholars based in United States. Mohammad Al-Rubaie's co-authors include J. Morris Chang and has published in prestigious journals such as IEEE Transactions on Information Forensics and Security, IEEE Security & Privacy and 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA).

In The Last Decade

Co-authorship network of co-authors of Mohammad Al-Rubaie i

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Fields of papers citing papers by Mohammad Al-Rubaie

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Al-Rubaie. 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 Mohammad Al-Rubaie. The network helps show where Mohammad Al-Rubaie may publish in the future.

Countries citing papers authored by Mohammad Al-Rubaie

Since Specialization

Citations

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

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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