Riccardo Zanella

895 citations
14 papers · 592 indexed · h-index 9

Riccardo Zanella

14 papers receiving 548 citations

Peers

Riccardo Zanella
Comparison fields: 5 of 59
  • Mathematical Physics 147
  • Structural Biology 23
  • Computational Mechanics 290
  • Numerical Analysis 76
  • Computer Vision and Pattern Recognition 227
Replace Matthew Fickus with:
Matthew Fickus United States
Silvia Bonettini Italy
Emmanuel Soubies France
Matthias J. Ehrhardt United Kingdom
Triet Le United States
Bernhard Schmitzer Germany
Martin Ehler Austria
Frank Filbir Germany
B.A. Mair United States
Stamatios Lefkimmiatis Switzerland
Riccardo Zanella relative to Matthew Fickus United States Matthew Fickus's profile →
Citations per field
00.5×3.8×
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Citations per year

Countries citing papers authored by Riccardo Zanella

Since Specialization
Citations

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

Fields of papers citing papers by Riccardo Zanella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Riccardo Zanella, 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 Riccardo Zanella Line = papers co-authored together Riccardo Zanella links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20173
2 20161
3 20161
4 201430
5 20141
6 201359
7 201317
8 20109
9 201083
10 200943
11 20092
12 2009113
13 200959
14 2008171

About Riccardo Zanella

Riccardo Zanella is a scholar working on Structural Biology, Mathematical Physics, Computer Vision and Pattern Recognition, Computational Mechanics and Biophysics, having authored 14 papers that have together received 592 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (6 papers), Numerical methods in inverse problems (5 papers), Image and Signal Denoising Methods (4 papers), Photoacoustic and Ultrasonic Imaging (4 papers), Medical Image Segmentation Techniques (3 papers), Medical Imaging Techniques and Applications (2 papers), Advanced Image Processing Techniques (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Mathematical Physics (147 citations), Structural Biology (23 citations), Computational Mechanics (290 citations), Numerical Analysis (76 citations) and Computer Vision and Pattern Recognition (227 citations). Riccardo Zanella has collaborated with scholars based in Italy, United States and Belgium. Frequent co-authors include Luca Zanni, M. Bertero, Silvia Bonettini, Patrizia Boccacci, Giorgio Talenti, Federico Benvenuto, Christine De Mol, Ignace Loris, Roberto Cavicchioli and Gaetano Zanghirati. Their work appears in journals such as Inverse Problems, Genome Medicine, Scientific Reports, Journal of Global Optimization and New Journal of Physics.

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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