Diego Dall’Alba
Impact in
- Health Informatics top 10%
- Biomedical Engineering top 10%
- Soft Robotics and Applications
- Anatomy and Medical Technology
Papers in
-
- Soft Robotics and Applications 20
- Anatomy and Medical Technology 12
- Surgery 23
- Surgical Simulation and Training 18
- Co-authors
- Paolo Fiorini (49 shared papers)Riccardo Muradore (7 shared papers)Arianna Menciassi (4 shared papers)Thiusius Rajeeth Savarimuthu (7 shared papers)Ole Jakob Elle (2 shared papers)Marco Piccinelli (3 shared papers)Kim Mathiassen (2 shared papers)Alı́cia Casals (5 shared papers)
In The Last Decade
Diego Dall’Alba
56 papers receiving 574 citations
Peers
Comparison fields: 5 of 81
- Health Informatics 20
- Biomedical Engineering 334
- Computer Vision and Pattern Recognition 122
- Control and Systems Engineering 125
- Surgery 192
Countries citing papers authored by Diego Dall’Alba
This map shows the geographic impact of Diego Dall’Alba'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 Diego Dall’Alba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Dall’Alba more than expected).
Fields of papers citing papers by Diego Dall’Alba
This network shows the impact of papers produced by Diego Dall’Alba. 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 Diego Dall’Alba. The network helps show where Diego Dall’Alba may publish in the future.
Co-authors
The 25 scholars most cited alongside Diego Dall’Alba, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 57 | |
| 2 | 2018 | 52 | |
| 3 | 2020 | 44 | |
| 4 | 2022 | 34 | |
| 5 | 2023 | 34 | |
| 6 | 2019 | 30 | |
| 7 | 2016 | 28 | |
| 8 | 2021 | 25 | |
| 9 | 2021 | 20 | |
| 10 | 2021 | 20 | |
| 11 | 2019 | 18 | |
| 12 | 2019 | 16 | |
| 13 | 2013 | 16 | |
| 14 | 2021 | 14 | |
| 15 | 2022 | 13 | |
| 16 | 2020 | 10 | |
| 17 | 2023 | 9 | |
| 18 | 2021 | 9 | |
| 19 | 2021 | 9 | |
| 20 | 2024 | 8 |
About Diego Dall’Alba
Diego Dall’Alba is a scholar working on Biomedical Engineering, Surgery, Computer Vision and Pattern Recognition, Control and Systems Engineering and Artificial Intelligence, having authored 59 papers that have together received 588 indexed citations. Recurring topics across this work include Soft Robotics and Applications (20 papers), Surgical Simulation and Training (18 papers), Anatomy and Medical Technology (12 papers), Robot Manipulation and Learning (9 papers), Reinforcement Learning in Robotics (6 papers), Electrical and Bioimpedance Tomography (6 papers), Body Composition Measurement Techniques (5 papers) and Ultrasound Imaging and Elastography (4 papers). The work is most often cited by research in Health Informatics (20 citations), Biomedical Engineering (334 citations), Computer Vision and Pattern Recognition (122 citations), Control and Systems Engineering (125 citations) and Surgery (192 citations). Diego Dall’Alba has collaborated with scholars based in Italy, France and Spain. Frequent co-authors include Paolo Fiorini, Riccardo Muradore, Arianna Menciassi, Thiusius Rajeeth Savarimuthu, Ole Jakob Elle, Marco Piccinelli, Kim Mathiassen, Alı́cia Casals, Cristians González and Jacques Marescaux. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, IEEE Robotics and Automation Letters, IEEE Transactions on Medical Robotics and Bionics, Measurement and The International Journal of Advanced Manufacturing 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.