Michael Mascagni

154 total papers · 2.1k total citations
79 papers, 1.2k citations indexed

About

Michael Mascagni is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Michael Mascagni has authored 79 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 17 papers in Computer Vision and Pattern Recognition and 14 papers in Computational Theory and Mathematics. Recurrent topics in Michael Mascagni's work include Chaos-based Image/Signal Encryption (16 papers), Mathematical Approximation and Integration (11 papers) and Parallel Computing and Optimization Techniques (9 papers). Michael Mascagni is often cited by papers focused on Chaos-based Image/Signal Encryption (16 papers), Mathematical Approximation and Integration (11 papers) and Parallel Computing and Optimization Techniques (9 papers). Michael Mascagni collaborates with scholars based in United States, South Korea and China. Michael Mascagni's co-authors include Ashok Srinivasan, Chi‐Ok Hwang, Yaohang Li, Nikolai A. Simonov, Jan Korst, Hongmei Chi, James A. Given, David M. Ceperley, Tony Warnock and Steven A. Cuccaro and has published in prestigious journals such as The Journal of Chemical Physics, Applied Physics Letters and Bioinformatics.

In The Last Decade

Michael Mascagni

76 papers receiving 1.1k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Michael Mascagni 242 236 212 174 150 79 1.2k
Elizabeth R. Jessup 277 1.1× 340 1.4× 102 0.5× 286 1.6× 92 0.6× 53 1.1k
Jonathan A. Kelner 370 1.5× 418 1.8× 311 1.5× 238 1.4× 160 1.1× 37 1.4k
Xiaobai Sun 126 0.5× 238 1.0× 415 2.0× 134 0.8× 170 1.1× 75 1.3k
Markus Hegland 108 0.4× 199 0.8× 112 0.5× 95 0.5× 65 0.4× 103 987
Luke N. Olson 95 0.4× 254 1.1× 93 0.4× 273 1.6× 201 1.3× 61 1.1k
Paul Hovland 289 1.2× 301 1.3× 111 0.5× 313 1.8× 113 0.8× 74 1.4k
Costas Bekas 281 1.2× 576 2.4× 70 0.3× 104 0.6× 397 2.6× 44 1.5k
Zlatko Drmač 247 1.0× 509 2.2× 103 0.5× 144 0.8× 78 0.5× 40 1.1k
Janusz S. Kowalik 222 0.9× 247 1.0× 75 0.4× 296 1.7× 169 1.1× 45 1.4k
James McKee 232 1.0× 462 2.0× 104 0.5× 200 1.1× 254 1.7× 32 1.2k

Countries citing papers authored by Michael Mascagni

Since Specialization
Citations

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

Fields of papers citing papers by Michael Mascagni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Mascagni

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

All Works

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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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