M.A. De Rosa

81 total papers · 1.0k total citations
61 papers, 830 citations indexed

About

M.A. De Rosa is a scholar working on Mechanics of Materials, Control and Systems Engineering and Civil and Structural Engineering. According to data from OpenAlex, M.A. De Rosa has authored 61 papers receiving a total of 830 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Mechanics of Materials, 35 papers in Control and Systems Engineering and 27 papers in Civil and Structural Engineering. Recurrent topics in M.A. De Rosa's work include Composite Structure Analysis and Optimization (39 papers), Vibration and Dynamic Analysis (32 papers) and Nonlocal and gradient elasticity in micro/nano structures (13 papers). M.A. De Rosa is often cited by papers focused on Composite Structure Analysis and Optimization (39 papers), Vibration and Dynamic Analysis (32 papers) and Nonlocal and gradient elasticity in micro/nano structures (13 papers). M.A. De Rosa collaborates with scholars based in Italy, Argentina and United States. M.A. De Rosa's co-authors include Maria Lippiello, N.M. Auciello, M.J. Maurizi, Stefania Tomasiello, Marcelo T. Piován, R.E. Rossi, Arcangelo Messina, Enrico Babilio, Isaac Elishakoff and Ram Jiwari and has published in prestigious journals such as SHILAP Revista de lepidopterología, Composites Part B Engineering and Journal of Sound and Vibration.

In The Last Decade

M.A. De Rosa

57 papers receiving 750 citations

Author Peers

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

Author						Papers	Cites
M.A. De Rosa	592	418	401	170	165	61	830
Chiung‐Shiann Huang	600 1.0×	578 1.4×	264 0.7×	144 0.8×	246 1.5×	47	987
M. Hemmatnezhad	577 1.0×	341 0.8×	214 0.5×	274 1.6×	130 0.8×	31	814
Danilo Capecchi	369 0.6×	645 1.5×	227 0.6×	95 0.6×	144 0.9×	65	1.0k
S. A. Eftekhari	622 1.1×	305 0.7×	323 0.8×	98 0.6×	154 0.9×	37	758
Ramazan‐Ali Jafari‐Talookolaei	621 1.0×	489 1.2×	317 0.8×	88 0.5×	183 1.1×	75	837
Dinh Kien Nguyen	819 1.4×	516 1.2×	348 0.9×	244 1.4×	193 1.2×	84	951
Ender Ciğeroğlu	267 0.5×	406 1.0×	266 0.7×	107 0.6×	295 1.8×	36	774
M. Fadaee	923 1.6×	595 1.4×	310 0.8×	296 1.7×	208 1.3×	37	1.0k
Majid Shahgholi	231 0.4×	447 1.1×	581 1.4×	125 0.7×	286 1.7×	57	882
L. Rubio	397 0.7×	554 1.3×	231 0.6×	117 0.7×	355 2.2×	44	868

Countries citing papers authored by M.A. De Rosa

Since Specialization

Citations

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

Fields of papers citing papers by M.A. De Rosa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.A. De Rosa. 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 M.A. De Rosa. The network helps show where M.A. De Rosa may publish in the future.

Co-authorship network of co-authors of M.A. De Rosa

This figure shows the co-authorship network connecting the top 25 collaborators of M.A. De Rosa. A scholar is included among the top collaborators of M.A. De Rosa 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 M.A. De Rosa. M.A. De Rosa 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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