Federico Iuricich
- Computational Theory and Mathematics top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Graphics and Computer-Aided Design top 5%
- Biophysics top 10%
- Signal Processing
- Co-authors
- Leila De FlorianiPaola MagilloHans HagenChristoph GarthGerik ScheuermannChristian HeineHeike LeitteMark W. Hlawitschka
- Topics
- Topological and Geometric Data Analysis (22 papers)Digital Image Processing Techniques (10 papers)Cell Image Analysis Techniques (7 papers)
- Partner nations
- United StatesItalySerbia
In The Last Decade
Federico Iuricich
26 papers receiving 253 citations
Peers
Comparison fields: 5 of 76
- Computational Theory and Mathematics 160
- Computer Vision and Pattern Recognition 138
- Computer Graphics and Computer-Aided Design 55
- Biophysics 47
- Signal Processing 40
Countries citing papers authored by Federico Iuricich
This map shows the geographic impact of Federico Iuricich'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 Federico Iuricich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico Iuricich more than expected).
Fields of papers citing papers by Federico Iuricich
This network shows the impact of papers produced by Federico Iuricich. 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 Federico Iuricich. The network helps show where Federico Iuricich may publish in the future.
Co-authorship network of co-authors of Federico Iuricich
This figure shows the co-authorship network connecting the top 25 collaborators of Federico Iuricich. A scholar is included among the top collaborators of Federico Iuricich based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Federico Iuricich. Federico Iuricich is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 11 | |
| 5 | 3 | |
| 6 | 9 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 5 | |
| 10 | 5 | |
| 11 | 7 | |
| 12 | 6 | |
| 13 | 8 | |
| 14 | 85 | |
| 15 | 2 | |
| 16 | 6 | |
| 17 | 4 | |
| 18 | 43 | |
| 19 | 5 | |
| 20 | 2 |
About Federico Iuricich
Federico Iuricich is a scholar working on Computational Theory and Mathematics, Biophysics and Computer Graphics and Computer-Aided Design, having authored 27 papers that have together received 262 indexed citations. Recurring topics across this work include Topological and Geometric Data Analysis (22 papers), Digital Image Processing Techniques (10 papers) and Cell Image Analysis Techniques (7 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (55 citations), Computational Theory and Mathematics (160 citations) and Biophysics (47 citations). Federico Iuricich has collaborated with scholars based in United States, Italy and Serbia. Frequent co-authors include Leila De Floriani, Paola Magillo, Hans Hagen, Christoph Garth, Gerik Scheuermann, Christian Heine, Heike Leitte, Mark W. Hlawitschka, Kenneth Weiss and Mark A. Eckert. Their work appears in journals such as Scientific Reports, PLoS Biology and Neuropsychologia.
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.