G. Sias

45 papers and 784 indexed citations i.

About

G. Sias is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, G. Sias has authored 45 papers receiving a total of 784 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Nuclear and High Energy Physics, 15 papers in Artificial Intelligence and 12 papers in Aerospace Engineering. Recurrent topics in G. Sias’s work include Magnetic confinement fusion research (22 papers), Time Series Analysis and Forecasting (8 papers) and Anomaly Detection Techniques and Applications (8 papers). G. Sias is often cited by papers focused on Magnetic confinement fusion research (22 papers), Time Series Analysis and Forecasting (8 papers) and Anomaly Detection Techniques and Applications (8 papers). G. Sias collaborates with scholars based in Italy, Germany and United Kingdom. G. Sias's co-authors include Alessandra Fanni, B. Cannas, Linda See, A. Pau, A. Murari, G. Pautasso, Sara Carcangiu, P. Sonato, F. Pisano and Stefania Tronci and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Power Delivery and Energies.

In The Last Decade

Co-authorship network of co-authors of G. Sias i

Fields of papers citing papers by G. Sias

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by G. Sias

Since Specialization
Citations

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