Matteo Saveriano
- Control and Systems Engineering top 2%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Mechanical Engineering
- Co-authors
- Dongheui LeeFares J. Abu‐DakkaLuka PeternelAljaž KrambergerRiccardo CaccavaleAlberto FinziPietro FalcoJustus Piater
- Topics
- Robot Manipulation and Learning (33 papers)Robotic Mechanisms and Dynamics (13 papers)Human Pose and Action Recognition (11 papers)
- Cited by
- Control and Systems EngineeringHuman-Computer InteractionComputer Vision and Pattern Recognition
- Journals
- PLoS ONEAutomaticaIEEE Access
In The Last Decade
Matteo Saveriano
58 papers receiving 599 citations
Hit Papers
Peers
Comparison fields: 5 of 64
- Control and Systems Engineering 391
- Computer Vision and Pattern Recognition 191
- Artificial Intelligence 161
- Biomedical Engineering 158
- Mechanical Engineering 75
Countries citing papers authored by Matteo Saveriano
This map shows the geographic impact of Matteo Saveriano'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 Saveriano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Saveriano more than expected).
Fields of papers citing papers by Matteo Saveriano
This network shows the impact of papers produced by Matteo Saveriano. 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 Saveriano. The network helps show where Matteo Saveriano may publish in the future.
Co-authorship network of co-authors of Matteo Saveriano
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Saveriano. A scholar is included among the top collaborators of Matteo Saveriano 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 Saveriano. Matteo Saveriano 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 | 0 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 12 | |
| 14 | 1 | |
| 15 | 7 | |
| 16 | 1 | |
| 17 | 5 | |
| 18 | 27 | |
| 19 | 23 | |
| 20 | The Role of Coupling Terms in Variable Impedance Policies Learning | 6 |
About Matteo Saveriano
Matteo Saveriano is a scholar working on Control and Systems Engineering, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 65 papers that have together received 609 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (33 papers), Robotic Mechanisms and Dynamics (13 papers) and Human Pose and Action Recognition (11 papers). The work is most often cited by research in Control and Systems Engineering (391 citations), Human-Computer Interaction (58 citations) and Computer Vision and Pattern Recognition (191 citations). Matteo Saveriano has collaborated with scholars based in Italy, Germany and Austria. Frequent co-authors include Dongheui Lee, Fares J. Abu‐Dakka, Luka Peternel, Aljaž Kramberger, Riccardo Caccavale, Alberto Finzi, Pietro Falco, Justus Piater, Raffaele Soloperto and Silvia Rossi. Their work appears in journals such as PLoS ONE, Automatica and IEEE Access.
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.