Suliman Mohamed Fati

63 papers and 1.0k indexed citations i.

About

Suliman Mohamed Fati is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Suliman Mohamed Fati has authored 63 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 12 papers in Computer Networks and Communications. Recurrent topics in Suliman Mohamed Fati’s work include AI in cancer detection (7 papers), IoT and Edge/Fog Computing (6 papers) and Caching and Content Delivery (5 papers). Suliman Mohamed Fati is often cited by papers focused on AI in cancer detection (7 papers), IoT and Edge/Fog Computing (6 papers) and Caching and Content Delivery (5 papers). Suliman Mohamed Fati collaborates with scholars based in Saudi Arabia, Malaysia and Pakistan. Suliman Mohamed Fati's co-authors include Amgad Muneer, Amjad Rehman, Ebrahim Mohammed Senan, Tanzila Saba, Saeed Ali Bahaj, Rao Faizan Ali, Muhammad Kashif, Sheraz Naseer, Ahmad Taher Azar and Ibrahim Abunadi and has published in prestigious journals such as PLoS ONE, Scientific Reports and Sensors.

In The Last Decade

Co-authorship network of co-authors of Suliman Mohamed Fati i

Fields of papers citing papers by Suliman Mohamed Fati

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Suliman Mohamed Fati. 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 Suliman Mohamed Fati. The network helps show where Suliman Mohamed Fati may publish in the future.

Countries citing papers authored by Suliman Mohamed Fati

Since Specialization
Citations

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

Explore authors with similar magnitude of impact

Rankless by CCL
2025