Edoardo Farnioli
- Biomedical Engineering top 5%
- Control and Systems Engineering top 2%
- Mechanical Engineering top 10%
- Cognitive Neuroscience top 10%
- Cellular and Molecular Neuroscience
- Co-authors
- Antonio BicchiManuel G. CatalanoGiorgio GrioliCristina PiazzaAlessandro SerioMarco GabicciniManolo GarabiniManuel Bonilla
- Topics
- Robot Manipulation and Learning (8 papers)Muscle activation and electromyography studies (6 papers)Soft Robotics and Applications (4 papers)
- Journals
- The International Journal of Robotics ResearchCINECA IRIS Institutial research information system (University of Pisa)
- Partner nations
- Italy
In The Last Decade
Edoardo Farnioli
10 papers receiving 744 citations
Hit Papers
Peers
Comparison fields: 5 of 43
- Biomedical Engineering 658
- Control and Systems Engineering 556
- Mechanical Engineering 185
- Cognitive Neuroscience 169
- Cellular and Molecular Neuroscience 51
Countries citing papers authored by Edoardo Farnioli
This map shows the geographic impact of Edoardo Farnioli'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 Edoardo Farnioli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edoardo Farnioli more than expected).
Fields of papers citing papers by Edoardo Farnioli
This network shows the impact of papers produced by Edoardo Farnioli. 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 Edoardo Farnioli. The network helps show where Edoardo Farnioli may publish in the future.
Co-authorship network of co-authors of Edoardo Farnioli
This figure shows the co-authorship network connecting the top 25 collaborators of Edoardo Farnioli. A scholar is included among the top collaborators of Edoardo Farnioli 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 Edoardo Farnioli. Edoardo Farnioli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 7 | |
| 3 | 13 | |
| 4 | Adaptive synergies for the design and control of the Pisa/IIT SoftHandbreakdown → | 483 |
| 5 | 52 | |
| 6 | 4 | |
| 7 | 24 | |
| 8 | 56 | |
| 9 | 18 | |
| 10 | 85 |
About Edoardo Farnioli
Edoardo Farnioli is a scholar working on Control and Systems Engineering, Biomedical Engineering and Cognitive Neuroscience, having authored 10 papers that have together received 759 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (8 papers), Muscle activation and electromyography studies (6 papers) and Soft Robotics and Applications (4 papers). The work is most often cited by research in Control and Systems Engineering (556 citations), Biomedical Engineering (658 citations) and Cognitive Neuroscience (169 citations). Edoardo Farnioli has collaborated with scholars based in Italy. Frequent co-authors include Antonio Bicchi, Manuel G. Catalano, Giorgio Grioli, Cristina Piazza, Alessandro Serio, Marco Gabiccini, Manolo Garabini, Manuel Bonilla, Gualtiero Fantoni and Lucia Pallottino. Their work appears in journals such as The International Journal of Robotics Research and CINECA IRIS Institutial research information system (University of Pisa).
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.