Paola Brianzi
- Mathematical Physics top 10%
- Applied Mathematics top 10%
- Atomic and Molecular Physics, and Optics
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Co-authors
- M. BerteroE. R. PikeM. FrontiniFabio Di BenedettoEdward Roy PikeClaudio EstaticoPaola FavatiFrancesco Romani
- Topics
- Numerical methods in inverse problems (10 papers)Image and Signal Denoising Methods (5 papers)Sparse and Compressive Sensing Techniques (3 papers)
- Partner nations
- ItalyIndiaUnited Kingdom
In The Last Decade
Paola Brianzi
15 papers receiving 237 citations
Peers
Comparison fields: 5 of 62
- Mathematical Physics 105
- Applied Mathematics 62
- Atomic and Molecular Physics, and Optics 59
- Biomedical Engineering 59
- Computer Vision and Pattern Recognition 55
Countries citing papers authored by Paola Brianzi
This map shows the geographic impact of Paola Brianzi'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 Paola Brianzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paola Brianzi more than expected).
Fields of papers citing papers by Paola Brianzi
This network shows the impact of papers produced by Paola Brianzi. 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 Paola Brianzi. The network helps show where Paola Brianzi may publish in the future.
Co-authorship network of co-authors of Paola Brianzi
This figure shows the co-authorship network connecting the top 25 collaborators of Paola Brianzi. A scholar is included among the top collaborators of Paola Brianzi 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 Paola Brianzi. Paola Brianzi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 14 | |
| 3 | 24 | |
| 4 | 16 | |
| 5 | 3 | |
| 6 | The 2D+1 method for an efficient modeling of collimator blur in 3D SPECT imaging | 1 |
| 7 | 15 | |
| 8 | 37 | |
| 9 | 22 | |
| 10 | 48 | |
| 11 | Positive regularised solutions in electromagnetic inverse scattering | 2 |
| 12 | Iterative inversion of experimental data in weighted spaces | 2 |
| 13 | 24 | |
| 14 | 32 | |
| 15 | 22 | |
| 16 | 26 | |
| 17 | 0 |
About Paola Brianzi
Paola Brianzi is a scholar working on Mathematical Physics, Applied Mathematics and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 289 indexed citations. Recurring topics across this work include Numerical methods in inverse problems (10 papers), Image and Signal Denoising Methods (5 papers) and Sparse and Compressive Sensing Techniques (3 papers). The work is most often cited by research in Mathematical Physics (105 citations), Biophysics (36 citations) and Applied Mathematics (62 citations). Paola Brianzi has collaborated with scholars based in Italy, India and United Kingdom. Frequent co-authors include M. Bertero, E. R. Pike, M. Frontini, Fabio Di Benedetto, Edward Roy Pike, Claudio Estatico, Paola Favati, Francesco Romani, Nicole Ostrowsky and Geoffrey de Villiers. Their work appears in journals such as The Journal of Chemical Physics, SIAM Journal on Scientific Computing and Inverse Problems.
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.