D. Ambrosi

4.8k citations
90 papers · 3.5k indexed · h-index 31

Impact in

Papers in

D. Ambrosi

87 papers receiving 3.4k citations

Peers

D. Ambrosi
Comparison fields: 5 of 141
  • Modeling and Simulation 759
  • Cell Biology 1.5k
  • Biomedical Engineering 1.7k
  • Fluid Flow and Transfer Processes 151
  • Computational Theory and Mathematics 294
Replace Sarah L. Waters with:
Sarah L. Waters United Kingdom
Martine Ben Amar France
Mark Alber United States
Luigi Preziosi Italy
Anne Hoger United States
Miloš Kojić Serbia
Alexandre Kabla United Kingdom
Krishna Garikipati United States
Mark H. Holmes United States
Pasquale Ciarletta Italy
D. Ambrosi relative to Sarah L. Waters United Kingdom Sarah L. Waters's profile →
Citations per field
00.5×3.5×
Sarah L. Waters · 1×
Citations per year

Countries citing papers authored by D. Ambrosi

Since Specialization
Citations

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

Fields of papers citing papers by D. Ambrosi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 2019156
2 20194
3 20182
4 20162
5 20151
6 201441
7 20123
8 2010347
9 20091
10
La matematica della bicicletta
20081
11 200725
12 20068
13
Mechanical aspects of growth in soft tissues
20041
14 2004103
15 2003187
16 200213
17 20028
18 200123
19
A 2D numerical simulation of the Po river delta flow
19942
20 19945

About D. Ambrosi

D. Ambrosi is a scholar working on Cell Biology, Modeling and Simulation, Fluid Flow and Transfer Processes, Biomedical Engineering and Computational Mechanics, having authored 90 papers that have together received 3.5k indexed citations. Recurring topics across this work include Cellular Mechanics and Interactions (39 papers), Elasticity and Material Modeling (24 papers), 3D Printing in Biomedical Research (11 papers), Force Microscopy Techniques and Applications (8 papers), Mathematical Biology Tumor Growth (8 papers), Cardiovascular Function and Risk Factors (7 papers), Advanced Numerical Methods in Computational Mathematics (7 papers) and Mechanical Circulatory Support Devices (7 papers). The work is most often cited by research in Modeling and Simulation (759 citations), Cell Biology (1.5k citations), Biomedical Engineering (1.7k citations), Fluid Flow and Transfer Processes (151 citations) and Computational Theory and Mathematics (294 citations). D. Ambrosi has collaborated with scholars based in Italy, France and United States. Frequent co-authors include Luigi Preziosi, Francesco Mollica, Simone Pezzuto, Alfio Quarteroni, Raimondo Penta, Claude Verdier, Ellen Kuhl, Jay D. Humphrey, Alain Goriely and Pasquale Ciarletta. Their work appears in journals such as SIAM Journal on Applied Mathematics, Journal of the Mechanics and Physics of Solids, Mathematical Models and Methods in Applied Sciences, Mathematics and Mechanics of Solids and Computer Methods in Biomechanics & Biomedical Engineering.

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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