Marco Prato

53 papers receiving 649 citations

Peers

Marco Prato
Comparison fields: 5 of 93
  • Numerical Analysis 96
  • Mathematical Physics 98
  • Computational Mechanics 220
  • Astronomy and Astrophysics 132
  • Computer Vision and Pattern Recognition 162
Replace A. Murli with:
A. Murli Italy
James H. Curry United States
Audrey Repetti United Kingdom
Riccardo March Italy
Shingyu Leung Hong Kong
Stefan Kunis Germany
Satyanad Kichenassamy France
Ronald E. Meyers United States
Philippe Tchamitchian France
Kang Feng China
Marco Prato relative to A. Murli Italy A. Murli's profile →
Citations per field
00.5×8.8×
A. Murli · 1×
Citations per year

Countries citing papers authored by Marco Prato

Since Specialization
Citations

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

Fields of papers citing papers by Marco Prato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Marco Prato, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marco Prato Line = papers co-authored together Marco Prato links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201973
2 201653
3 201151
4 201141
5 201235
6 200433
7 200732
8 200927
9 201725
10 201523
11 200821
12 201020
13 201320
14 202319
15 200718
16 201818
17 202017
18 201116
19 200615
20 202012

About Marco Prato

Marco Prato is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Artificial Intelligence, Mathematical Physics and Biomedical Engineering, having authored 57 papers that have together received 694 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (27 papers), Numerical methods in inverse problems (13 papers), Image and Signal Denoising Methods (12 papers), Advanced Image Processing Techniques (9 papers), Solar and Space Plasma Dynamics (9 papers), Photoacoustic and Ultrasonic Imaging (8 papers), Advanced Optimization Algorithms Research (8 papers) and Solar Radiation and Photovoltaics (6 papers). The work is most often cited by research in Numerical Analysis (96 citations), Mathematical Physics (98 citations), Computational Mechanics (220 citations), Astronomy and Astrophysics (132 citations) and Computer Vision and Pattern Recognition (162 citations). Marco Prato has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Silvia Bonettini, Luca Zanni, Federica Porta, Michele Piana, Anna Maria Massone, A. G. Emslie, Eduard P. Kontar, Ignace Loris, Émilie Chouzenoux and Jean‐Christophe Pesquet. Their work appears in journals such as Inverse Problems, Computational Optimization and Applications, The Astrophysical Journal, Applied Mathematics and Computation and Journal of Scientific Computing.

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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