Marco Gabiccini
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- Robot Manipulation and Learning 26
- Robotic Mechanisms and Dynamics 13
- Iterative Learning Control Systems 9
- Mechanical Engineering top 2%
- Gear and Bearing Dynamics Analysis 25
- Tribology and Lubrication Engineering 14
- Cognitive Neuroscience top 5%
- Motor Control and Adaptation 8
- Human-Computer Interaction top 5%
- Biomedical Engineering top 5%
- Muscle activation and electromyography studies 13
- Soft Robotics and Applications 9
- Co-authors
- Antonio BicchiAlessio ArtoniMassimo GuiggianiDomenico PrattichizzoMarco SantelloMonica MalvezziMatteo BianchiFrancesca Di Puccio
- Journals
- Mechanism and Machine Theory (8 papers)Journal of Mechanical Design (6 papers)IEEE Robotics and Automation Letters (3 papers)
- Partner nations
- ItalyUnited StatesGermany
In The Last Decade
Marco Gabiccini
74 papers receiving 2.0k citations
Peers
Comparison fields: 5 of 89
- Control and Systems Engineering 995
- Mechanical Engineering 874
- Cognitive Neuroscience 448
- Human-Computer Interaction 116
- Biomedical Engineering 885
Countries citing papers authored by Marco Gabiccini
This map shows the geographic impact of Marco Gabiccini'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 Marco Gabiccini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Gabiccini more than expected).
Fields of papers citing papers by Marco Gabiccini
This network shows the impact of papers produced by Marco Gabiccini. 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 Marco Gabiccini. The network helps show where Marco Gabiccini may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marco Gabiccini, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 9 | |
| 5 | 2021 | 8 | |
| 6 | 2020 | 2 | |
| 7 | 2020 | 38 | |
| 8 | 2019 | 18 | |
| 9 | 2018 | 14 | |
| 10 | 2016 | 1 | |
| 11 | Data-driven human grasp movement analysis | 2016 | 3 |
| 12 | 2016 | 15 | |
| 13 | 2016 | 12 | |
| 14 | 2016 | 98 | |
| 15 | 2014 | 9 | |
| 16 | 2013 | 22 | |
| 17 | 2012 | 41 | |
| 18 | The Hand Embodied | 2011 | 1 |
| 19 | 2010 | 78 | |
| 20 | 2008 | 103 |
About Marco Gabiccini
Marco Gabiccini is a scholar working on Control and Systems Engineering, Mechanical Engineering and Cognitive Neuroscience, having authored 77 papers that have together received 2.0k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (26 papers), Gear and Bearing Dynamics Analysis (25 papers), Tribology and Lubrication Engineering (14 papers), Muscle activation and electromyography studies (13 papers), Robotic Mechanisms and Dynamics (13 papers), Soft Robotics and Applications (9 papers), Iterative Learning Control Systems (9 papers) and Motor Control and Adaptation (8 papers). The work is most often cited by research in Control and Systems Engineering (995 citations), Mechanical Engineering (874 citations) and Cognitive Neuroscience (448 citations). Marco Gabiccini has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Antonio Bicchi, Alessio Artoni, Massimo Guiggiani, Domenico Prattichizzo, Marco Santello, Monica Malvezzi, Matteo Bianchi, Francesca Di Puccio, Edoardo Farnioli and Gabriele Pannocchia. Their work appears in journals such as Mechanism and Machine Theory, Journal of Mechanical Design, IEEE Robotics and Automation Letters, Physics of Life Reviews and Multibody System Dynamics.
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.