Matteo Panciroli
- Automotive Engineering top 5%
- Computer Vision and Pattern Recognition top 10%
- Control and Systems Engineering top 10%
- Aerospace Engineering
- Electrical and Electronic Engineering
- Co-authors
- Alberto BroggiPaolo MediciStefano DebattistiPaolo ZaniMaria Chiara LaghiAntonio PriolettiPietro CerriLuca Mazzei
- Topics
- Autonomous Vehicle Technology and Safety (6 papers)Robotic Path Planning Algorithms (4 papers)Real-Time Systems Scheduling (2 papers)
- Cited by
- Automotive EngineeringComputer Vision and Pattern RecognitionControl and Systems Engineering
- Journals
- IEEE Transactions on Intelligent Transportation SystemsAnnual Reviews in ControlInternational Journal of Automotive Technology
- Partner nations
- Italy
In The Last Decade
Matteo Panciroli
8 papers receiving 265 citations
Peers
Comparison fields: 5 of 46
- Automotive Engineering 181
- Computer Vision and Pattern Recognition 132
- Control and Systems Engineering 95
- Aerospace Engineering 66
- Electrical and Electronic Engineering 33
Countries citing papers authored by Matteo Panciroli
This map shows the geographic impact of Matteo Panciroli'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 Panciroli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Panciroli more than expected).
Fields of papers citing papers by Matteo Panciroli
This network shows the impact of papers produced by Matteo Panciroli. 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 Panciroli. The network helps show where Matteo Panciroli may publish in the future.
Co-authorship network of co-authors of Matteo Panciroli
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Panciroli. A scholar is included among the top collaborators of Matteo Panciroli 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 Panciroli. Matteo Panciroli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 68 | |
| 3 | 55 | |
| 4 | 39 | |
| 5 | 8 | |
| 6 | 7 | |
| 7 | 85 | |
| 8 | 5 |
About Matteo Panciroli
Matteo Panciroli is a scholar working on Automotive Engineering, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 272 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (6 papers), Robotic Path Planning Algorithms (4 papers) and Real-Time Systems Scheduling (2 papers). The work is most often cited by research in Automotive Engineering (181 citations), Computer Vision and Pattern Recognition (132 citations) and Control and Systems Engineering (95 citations). Matteo Panciroli has collaborated with scholars based in Italy. Frequent co-authors include Alberto Broggi, Paolo Medici, Stefano Debattisti, Paolo Zani, Maria Chiara Laghi, Antonio Prioletti, Pietro Cerri, Luca Mazzei, Daniele Molinari and Pier Paolo Porta. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Annual Reviews in Control and International Journal of Automotive Technology.
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.