Leonardo Robol

834 citations
53 papers · 512 · h-index 13

Impact in

Papers in

Leonardo Robol

49 papers receiving 498 citations

Peers

Leonardo Robol
Comparison fields: 5 of 67
  • Computational Mathematics 43
  • Numerical Analysis 104
  • Computational Theory and Mathematics 250
  • Statistics, Probability and Uncertainty 56
  • Statistical and Nonlinear Physics 75
Replace Ninoslav Truhar with:
Ninoslav Truhar Croatia
Eric King‐wah Chu Australia
Silvia Noschese Italy
Heike Faßbender Germany
Yiqin Lin China
A. Bouhamidi France
Guang-Xin Huang China
Michael Eiermann Germany
David Day United States
Huaian Diao China
Leonardo Robol relative to Ninoslav Truhar Croatia Ninoslav Truhar's profile →
Citations per field
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Ninoslav Truhar · 1×
Citations per year

Countries citing papers authored by Leonardo Robol

Since Specialization
Citations

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

Fields of papers citing papers by Leonardo Robol

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201361
2 202051
3 201939
4 202029
5 201826
6 201922
7 201722
8 201819
9 201918
10 202016
11 201914
12 202213
13 201613
14 201712
15 201812
16 201912
17 202012
18 201712
19 201611
20 201811

About Leonardo Robol

Leonardo Robol is a scholar working on Computational Theory and Mathematics, Numerical Analysis, Computational Mathematics, Statistics, Probability and Uncertainty and Statistical and Nonlinear Physics, having authored 53 papers that have together received 512 indexed citations. Recurring topics across this work include Matrix Theory and Algorithms (33 papers), Tensor decomposition and applications (10 papers), Structural Health Monitoring Techniques (9 papers), Advanced Optimization Algorithms Research (8 papers), Electromagnetic Scattering and Analysis (7 papers), Numerical methods for differential equations (7 papers), Polynomial and algebraic computation (7 papers) and Numerical Methods and Algorithms (6 papers). The work is most often cited by research in Computational Mathematics (43 citations), Numerical Analysis (104 citations), Computational Theory and Mathematics (250 citations), Statistics, Probability and Uncertainty (56 citations) and Statistical and Nonlinear Physics (75 citations). Leonardo Robol has collaborated with scholars based in Italy, Switzerland and Belgium. Frequent co-authors include Stefano Massei, Dario A. Bini, Daniele Pellegrini, Maria Girardi, Cristina Padovani, Daniel Kreßner, Raf Vandebril, Margherita Porcelli, Paul Van Dooren and David S. Watkins. Their work appears in journals such as SIAM Journal on Matrix Analysis and Applications, Linear Algebra and its Applications, SIAM Journal on Scientific Computing, Numerical Algorithms and Journal of Computational and Applied Mathematics.

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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