Matteo Ragaglia
- Control and Systems Engineering top 5%
- Computer Vision and Pattern Recognition top 10%
- Mechanical Engineering
- Biomedical Engineering
- Industrial and Manufacturing Engineering top 10%
- Co-authors
- Paolo RoccoAndrea Maria ZanchettinAmir M. Ghalamzan E.Marta NiccoliniLuca BascettaCarlo Alberto AvizzanoFabrizio ArgentiAlessandro Piva
- Topics
- Robot Manipulation and Learning (8 papers)Teleoperation and Haptic Systems (5 papers)Robotic Path Planning Algorithms (4 papers)
- Cited by
- Control and Systems EngineeringIndustrial and Manufacturing EngineeringComputer Vision and Pattern Recognition
- Journals
- Robotics and Autonomous SystemsRobotics and Computer-Integrated ManufacturingIEEE Robotics and Automation Letters
- Partner nations
- ItalyUnited Kingdom
In The Last Decade
Matteo Ragaglia
19 papers receiving 338 citations
Peers
Comparison fields: 5 of 46
- Control and Systems Engineering 197
- Computer Vision and Pattern Recognition 117
- Mechanical Engineering 88
- Biomedical Engineering 76
- Industrial and Manufacturing Engineering 57
Countries citing papers authored by Matteo Ragaglia
This map shows the geographic impact of Matteo Ragaglia'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 Ragaglia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Ragaglia more than expected).
Fields of papers citing papers by Matteo Ragaglia
This network shows the impact of papers produced by Matteo Ragaglia. 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 Ragaglia. The network helps show where Matteo Ragaglia may publish in the future.
Co-authorship network of co-authors of Matteo Ragaglia
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Ragaglia. A scholar is included among the top collaborators of Matteo Ragaglia 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 Ragaglia. Matteo Ragaglia 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 | 3 | |
| 3 | 9 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 65 | |
| 8 | 48 | |
| 9 | 43 | |
| 10 | 19 | |
| 11 | 6 | |
| 12 | 20 | |
| 13 | 16 | |
| 14 | 3 | |
| 15 | 36 | |
| 16 | 7 | |
| 17 | 5 | |
| 18 | 41 | |
| 19 | 17 | |
| 20 | 6 |
About Matteo Ragaglia
Matteo Ragaglia is a scholar working on Control and Systems Engineering, Radiological and Ultrasound Technology and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 348 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (8 papers), Teleoperation and Haptic Systems (5 papers) and Robotic Path Planning Algorithms (4 papers). The work is most often cited by research in Control and Systems Engineering (197 citations), Industrial and Manufacturing Engineering (57 citations) and Computer Vision and Pattern Recognition (117 citations). Matteo Ragaglia has collaborated with scholars based in Italy and United Kingdom. Frequent co-authors include Paolo Rocco, Andrea Maria Zanchettin, Amir M. Ghalamzan E., Marta Niccolini, Luca Bascetta, Carlo Alberto Avizzano, Fabrizio Argenti, Alessandro Piva, Francesca Uccheddu and Pasquale Ferrara. Their work appears in journals such as Robotics and Autonomous Systems, Robotics and Computer-Integrated Manufacturing and IEEE Robotics and Automation Letters.
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.