Maria Riccio
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 10%
- Aerospace Engineering top 10%
- Media Technology top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Pasquale DaponteLuca De VitoFrancesco PicarielloSergio RapuanoFrancesco LamonacaDomenico GrimaldiDomenico Luca CarnìG. Andria
- Topics
- Experimental Learning in Engineering (9 papers)Advanced MEMS and NEMS Technologies (4 papers)Energy Efficient Wireless Sensor Networks (4 papers)
In The Last Decade
Maria Riccio
26 papers receiving 463 citations
Peers
Comparison fields: 5 of 106
- Electrical and Electronic Engineering 133
- Computer Vision and Pattern Recognition 112
- Aerospace Engineering 105
- Media Technology 91
- Computer Networks and Communications 89
Countries citing papers authored by Maria Riccio
This map shows the geographic impact of Maria Riccio'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 Maria Riccio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maria Riccio more than expected).
Fields of papers citing papers by Maria Riccio
This network shows the impact of papers produced by Maria Riccio. 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 Maria Riccio. The network helps show where Maria Riccio may publish in the future.
Co-authorship network of co-authors of Maria Riccio
This figure shows the co-authorship network connecting the top 25 collaborators of Maria Riccio. A scholar is included among the top collaborators of Maria Riccio 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 Maria Riccio. Maria Riccio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 8 | |
| 3 | 11 | |
| 4 | 11 | |
| 5 | 27 | |
| 6 | 39 | |
| 7 | 3 | |
| 8 | 35 | |
| 9 | 69 | |
| 10 | 6 | |
| 11 | 71 | |
| 12 | 6 | |
| 13 | 27 | |
| 14 | 29 | |
| 15 | 1 | |
| 16 | 8 | |
| 17 | 12 | |
| 18 | 15 | |
| 19 | 7 | |
| 20 | A remote laboratory for electric measurement experiments: the remote displaying of instruments | 6 |
About Maria Riccio
Maria Riccio is a scholar working on Media Technology, Human-Computer Interaction and Hardware and Architecture, having authored 26 papers that have together received 480 indexed citations. Recurring topics across this work include Experimental Learning in Engineering (9 papers), Advanced MEMS and NEMS Technologies (4 papers) and Energy Efficient Wireless Sensor Networks (4 papers). The work is most often cited by research in Media Technology (91 citations), Human-Computer Interaction (35 citations) and Computer Vision and Pattern Recognition (112 citations). Maria Riccio has collaborated with scholars based in Italy, Croatia and Germany. Frequent co-authors include Pasquale Daponte, Luca De Vito, Francesco Picariello, Sergio Rapuano, Francesco Lamonaca, Domenico Grimaldi, Domenico Luca Carnì, G. Andria, Lorenzo Peretto and A. Nastro. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Measurement and IEEE Instrumentation & Measurement Magazine.
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.