S. Dahbi

6 papers and 13 indexed citations i.

About

S. Dahbi is a scholar working on Artificial Intelligence, Nuclear and High Energy Physics and Modeling and Simulation. According to data from OpenAlex, S. Dahbi has authored 6 papers receiving a total of 13 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 3 papers in Nuclear and High Energy Physics and 2 papers in Modeling and Simulation. Recurrent topics in S. Dahbi’s work include Particle physics theoretical and experimental studies (3 papers), Computational Physics and Python Applications (2 papers) and COVID-19 epidemiological studies (2 papers). S. Dahbi is often cited by papers focused on Particle physics theoretical and experimental studies (3 papers), Computational Physics and Python Applications (2 papers) and COVID-19 epidemiological studies (2 papers). S. Dahbi collaborates with scholars based in South Africa, Canada and Italy. S. Dahbi's co-authors include B. Mellado, Andreas Crivellin, C. A. Manzari, Ali Asgary, X. Ruan, James Orbinski, Turgay Çelik, Mary Kawonga, Jian Wu and Kentaro Hayashi and has published in prestigious journals such as Physical review. D, International Journal of Modern Physics A and BMC Medical Informatics and Decision Making.

In The Last Decade

Co-authorship network of co-authors of S. Dahbi i

Fields of papers citing papers by S. Dahbi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by S. Dahbi

Since Specialization
Citations

This map shows the geographic impact of S. Dahbi'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 S. Dahbi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Dahbi 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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2025