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 9
- Surgery 21
- Surgical Simulation and Training 16
- Hemodynamic Monitoring and Therapy 4
- Co-authors
- Paolo Fiorini (49 shared papers)Riccardo Muradore (8 shared papers)Thiusius Rajeeth Savarimuthu (7 shared papers)Arianna Menciassi (4 shared papers)Alı́cia Casals (5 shared papers)Cristians González (4 shared papers)Didier Mutter (4 shared papers)Ole Jakob Elle (2 shared papers)
In The Last Decade
Diego Dall’Alba
57 papers receiving 617 citations
Peers
Comparison fields: 5 of 79
- Health Informatics 18
- Biomedical Engineering 327
- Computer Vision and Pattern Recognition 125
- Control and Systems Engineering 128
- 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 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 59 | |
| 2 | 2018 | 53 | |
| 3 | 2020 | 48 | |
| 4 | 2022 | 40 | |
| 5 | 2023 | 35 | |
| 6 | 2019 | 30 | |
| 7 | 2021 | 28 | |
| 8 | 2016 | 28 | |
| 9 | 2021 | 23 | |
| 10 | 2021 | 22 | |
| 11 | 2019 | 18 | |
| 12 | 2019 | 16 | |
| 13 | 2013 | 16 | |
| 14 | 2021 | 14 | |
| 15 | 2022 | 14 | |
| 16 | 2024 | 12 | |
| 17 | 2024 | 11 | |
| 18 | 2020 | 10 | |
| 19 | 2021 | 10 | |
| 20 | 2021 | 9 |
About Diego Dall’Alba
Diego Dall’Alba is a scholar working on Biomedical Engineering, Surgery, Control and Systems Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 60 papers that have together received 631 indexed citations. Recurring topics across this work include Soft Robotics and Applications (20 papers), Surgical Simulation and Training (16 papers), Anatomy and Medical Technology (9 papers), Robot Manipulation and Learning (9 papers), Electrical and Bioimpedance Tomography (6 papers), Reinforcement Learning in Robotics (6 papers), Body Composition Measurement Techniques (5 papers) and Hemodynamic Monitoring and Therapy (4 papers). The work is most often cited by research in Health Informatics (18 citations), Biomedical Engineering (327 citations), Computer Vision and Pattern Recognition (125 citations), Control and Systems Engineering (128 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, Thiusius Rajeeth Savarimuthu, Arianna Menciassi, Alı́cia Casals, Cristians González, Didier Mutter, Ole Jakob Elle, Nicolas Padoy 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, Applied Intelligence and Medical Image Analysis.
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.