Matteo Santoro
- Computer Vision and Pattern Recognition top 10%
- Molecular Biology
- Neurology
- Neurology top 10%
- Artificial Intelligence
- Co-authors
- Lorenzo RosascoAlessandro VerriSofia MosciSilvia VillaPeter TeismannGernot RiedelJohn V. ForresterHeather L. Martin
- Topics
- Sparse and Compressive Sensing Techniques (5 papers)Parkinson's Disease Mechanisms and Treatments (4 papers)Nerve injury and regeneration (3 papers)
- Cited by
- NeurologyClinical Biochemistry
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Matteo Santoro
27 papers receiving 497 citations
Peers
Comparison fields: 5 of 104
- Computer Vision and Pattern Recognition 101
- Molecular Biology 92
- Neurology 87
- Neurology 79
- Artificial Intelligence 71
Countries citing papers authored by Matteo Santoro
This map shows the geographic impact of Matteo Santoro'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 Matteo Santoro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Santoro more than expected).
Fields of papers citing papers by Matteo Santoro
This network shows the impact of papers produced by Matteo Santoro. 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 Matteo Santoro. The network helps show where Matteo Santoro may publish in the future.
Co-authorship network of co-authors of Matteo Santoro
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Santoro. A scholar is included among the top collaborators of Matteo Santoro 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 Matteo Santoro. Matteo Santoro 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 | 19 | |
| 3 | 41 | |
| 4 | 82 | |
| 5 | 6 | |
| 6 | 15 | |
| 7 | 16 | |
| 8 | 10 | |
| 9 | 14 | |
| 10 | 3 | |
| 11 | A Regularization Approach to Nonlinear Variable Selection | 9 |
| 12 | Iterative Projection Methods for Structured Sparsity Regularization | 63 |
| 13 | 6 | |
| 14 | Unsupervised Learning of Behavioural Patterns for Video-Surveillance | 2 |
| 15 | 6 | |
| 16 | 8 | |
| 17 | 3 | |
| 18 | 3 | |
| 19 | 23 | |
| 20 | 29 |
About Matteo Santoro
Matteo Santoro is a scholar working on Computer Vision and Pattern Recognition, Neurology and Computational Mechanics, having authored 29 papers that have together received 512 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (5 papers), Parkinson's Disease Mechanisms and Treatments (4 papers) and Nerve injury and regeneration (3 papers). The work is most often cited by research in Neurology (79 citations), Clinical Biochemistry (52 citations) and Neurology (87 citations). Matteo Santoro has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Lorenzo Rosasco, Alessandro Verri, Sofia Mosci, Silvia Villa, Peter Teismann, Gernot Riedel, John V. Forrester, Heather L. Martin, Sarah Mustafa and Guglielmo Tamburrini. Their work appears in journals such as Journal of Applied Physics, Brain Research and IEEE Transactions on Image Processing.
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.