Fabio Ancona

46 papers receiving 402 citations

Peers

Fabio Ancona
Comparison fields: 5 of 56
  • Applied Mathematics 194
  • Mathematical Physics 118
  • Control and Systems Engineering 252
  • Geometry and Topology 39
  • Computational Mechanics 89
Replace Dmitry Vorotnikov with:
Dmitry Vorotnikov Portugal
Andrey Sarychev Russia
Massimo Gobbino Italy
В. И. Максимов Russia
J. Barros-Neto United States
Yu. S. Osipov Russia
Vadim Adamjan Ukraine
Ludovic Rifford France
Alexander Borichev France
Fabio Ancona relative to Dmitry Vorotnikov Portugal Dmitry Vorotnikov's profile →
Citations per field
00.5×1.5×2.3×
Dmitry Vorotnikov · 1×
Citations per year

Countries citing papers authored by Fabio Ancona

Since Specialization
Citations

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

Fields of papers citing papers by Fabio Ancona

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199988
2 199864
3 200528
4 200227
5 199726
6 199919
7 200116
8 200215
9 200715
10 200113
11 201913
12 200411
13 201210
14 20028
15 20047
16 20077
17 20117
18 20056
19 20065
20 20085

About Fabio Ancona

Fabio Ancona is a scholar working on Applied Mathematics, Control and Systems Engineering, Artificial Intelligence, Mathematical Physics and Computer Vision and Pattern Recognition, having authored 52 papers that have together received 450 indexed citations. Recurring topics across this work include Navier-Stokes equation solutions (24 papers), Stability and Controllability of Differential Equations (16 papers), Neural Networks and Applications (14 papers), Advanced Mathematical Physics Problems (13 papers), Image and Signal Denoising Methods (8 papers), Advanced Data Compression Techniques (7 papers), Computational Fluid Dynamics and Aerodynamics (6 papers) and Advanced Differential Equations and Dynamical Systems (6 papers). The work is most often cited by research in Applied Mathematics (194 citations), Mathematical Physics (118 citations), Control and Systems Engineering (252 citations), Geometry and Topology (39 citations) and Computational Mechanics (89 citations). Fabio Ancona has collaborated with scholars based in Italy, United States and France. Frequent co-authors include Andrea Marson, Alberto Bressan, Giuseppe Maria Coclite, Rodolfo Zunino, Stefano Rovetta, Paola Goatin, A.M. Colla, Khai T. Nguyen, Olivier Glass and Alessio Porretta. Their work appears in journals such as SIAM Journal on Control and Optimization, ESAIM Control Optimisation and Calculus of Variations, Annales de l Institut Henri Poincaré C Analyse Non Linéaire, Nonlinear Analysis and Journal of Differential Equations.

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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