Roberto Susino

1.4k total citations
45 papers, 391 citations indexed

About

Roberto Susino is a scholar working on Astronomy and Astrophysics, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Roberto Susino has authored 45 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Astronomy and Astrophysics, 8 papers in Molecular Biology and 6 papers in Artificial Intelligence. Recurrent topics in Roberto Susino's work include Solar and Space Plasma Dynamics (42 papers), Stellar, planetary, and galactic studies (26 papers) and Ionosphere and magnetosphere dynamics (24 papers). Roberto Susino is often cited by papers focused on Solar and Space Plasma Dynamics (42 papers), Stellar, planetary, and galactic studies (26 papers) and Ionosphere and magnetosphere dynamics (24 papers). Roberto Susino collaborates with scholars based in Italy, United States and Germany. Roberto Susino's co-authors include А. Бемпорад, D. Spadaro, Salvatore Mancuso, S. Jejčič, P. Heinzel, A. Vourlidas, Silvano Fineschi, R. Ventura, E. Landi and Daniele Telloni and has published in prestigious journals such as The Astrophysical Journal, Astronomy and Astrophysics and Physics of Plasmas.

In The Last Decade

Roberto Susino

41 papers receiving 349 citations

Peers

Roberto Susino

EEE

Karin Dissauer Austria

L. Bone United Kingdom

Xianyong Bai China

Igor Khazanov United States

S. Vargas Domínguez Colombia

V. M. J. Henriques Norway

E. Mazy Belgium

Rok-Soon Kim South Korea

Jürgen Hinterreiter Austria

C. Kuckein Germany

Karin Dissauer Austria

Roberto Susino

445 ×1.2

91 ×1.1

70 ×1.6

14 ×1.1

EEE

9 ×0.8

Citations per year, relative to Roberto Susino Roberto Susino (= 1×) peers Karin Dissauer

Countries citing papers authored by Roberto Susino

Since Specialization

Citations

This map shows the geographic impact of Roberto Susino'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 Roberto Susino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto Susino more than expected).

Fields of papers citing papers by Roberto Susino

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Roberto Susino. 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 Roberto Susino. The network helps show where Roberto Susino may publish in the future.

Co-authorship network of co-authors of Roberto Susino

This figure shows the co-authorship network connecting the top 25 collaborators of Roberto Susino. A scholar is included among the top collaborators of Roberto Susino 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 Roberto Susino. Roberto Susino is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Giordano, S., D. Spadaro, Roberto Susino, et al.. (2025). Solar wind speed maps from the Metis coronagraph observations. Astronomy and Astrophysics. 701. A56–A56.

Susino, Roberto, David H. Brooks, R. Lionello, et al.. (2025). Investigating Solar Wind Outflows from Open–Closed Magnetic Field Structures Using Coordinated Solar Orbiter and Hinode Observations. Solar Physics. 300(4). 45–45. 1 indexed citations

Vásquez, A. M., A. Burtovoi, P. Lamy, et al.. (2025). Photometric Comparison of Metis and LASCO-C2 Polarized Brightness Images. Solar Physics. 300(1). 2 indexed citations

Uslenghi, M., V. Andretta, K. Heerlein, et al.. (2024). Characterization of the dark signal of the Solar Orbiter/Metis detectors. Florence Research (University of Florence). 126–126. 1 indexed citations

Vásquez, A. M., M. Romoli, P. Lamy, et al.. (2024). Tomography of the Solar Corona with the Metis Coronagraph II: Three-Dimensional Reconstructions of the Electron Density and Comparison with Reconstructions Based on LASCO-C2. Solar Physics. 299(12). 2 indexed citations

Perracchione, Emma, Daniele Telloni, Roberto Susino, et al.. (2024). Forecasting Geoffective Events from Solar Wind Data and Evaluating the Most Predictive Features through Machine Learning Approaches. The Astrophysical Journal. 971(1). 94–94. 4 indexed citations

Бемпорад, А., Francesco Marchetti, Federico Benvenuto, et al.. (2023). Physics-driven Machine Learning for the Prediction of Coronal Mass Ejections’ Travel Times. The Astrophysical Journal. 954(2). 151–151. 11 indexed citations

Telloni, Daniele, Enrico Magli, Silvano Fineschi, et al.. (2023). Prediction Capability of Geomagnetic Events from Solar Wind Data Using Neural Networks. The Astrophysical Journal. 952(2). 111–111. 8 indexed citations

Capobianco, Gerardo, Silvano Fineschi, G. Massone, et al.. (2023). Sky Brightness Evaluation and First Coronal Signal Detection from Concordia Base (Antarctica) with a Calibrated Micropolarizer Array Camera. Solar Physics. 298(10). 1 indexed citations

10.

Niembro, Tatiana, Daniel B. Seaton, Phillip Hess, et al.. (2023). A prominence eruption from the Sun to the Parker Solar Probe with multi-spacecraft observations. Frontiers in Astronomy and Space Sciences. 10. 6 indexed citations

11.

Capobianco, Gerardo, Silvano Fineschi, G. Massone, et al.. (2022). Sky Brightness Evaluation at Concordia Station, Dome C, Antarctica, for Ground-Based Observations of the Solar Corona. Solar Physics. 297(3). 29–29. 4 indexed citations

12.

Frassati, F., Monica Laurenza, А. Бемпорад, et al.. (2022). Acceleration of Solar Energetic Particles through CME-driven Shock and Streamer Interaction. The Astrophysical Journal. 926(2). 227–227. 7 indexed citations

13.

Zhao, Jie, S. E. Gibson, Silvano Fineschi, et al.. (2021). Simulating the Solar Minimum Corona in UV Wavelengths with Forward Modeling II. Doppler Dimming and Microscopic Anisotropy Effect. The Astrophysical Journal. 912(2). 141–141. 11 indexed citations

14.

Heinzel, P., Jiří Štěpán, А. Бемпорад, et al.. (2020). On the Possibility of Detecting Helium D3 Line Polarization with Metis. The Astrophysical Journal. 900(1). 8–8. 5 indexed citations

15.

Frassati, F., Roberto Susino, Salvatore Mancuso, & А. Бемпорад. (2019). Comprehensive Analysis of the Formation of a Shock Wave Associated with a Coronal Mass Ejection. The Astrophysical Journal. 871(2). 212–212. 17 indexed citations

16.

Telloni, Daniele, E. Antonucci, А. Бемпорад, et al.. (2019). Detection of Coronal Mass Ejections at L1 and Forecast of Their Geoeffectiveness. The Astrophysical Journal. 885(2). 120–120. 18 indexed citations

17.

Frassati, F., Roberto Susino, Salvatore Mancuso, & А. Бемпорад. (2019). Kinematics of a compression front associated with a Coronal Mass Ejection. 42(1). 35. 1 indexed citations

18.

Zhao, Jie, S. E. Gibson, Silvano Fineschi, et al.. (2019). Simulating the Solar Corona in the Forbidden and Permitted Lines with Forward Modeling. I. Saturated and Unsaturated Hanle Regimes. The Astrophysical Journal. 883(1). 55–55. 12 indexed citations

19.

Susino, Roberto, А. Бемпорад, S. Jejčič, & P. Heinzel. (2018). Hot prominence detected in the core of a Coronal Mass Ejection: III. Plasma filling factor from UVCS Lyman-$α$ and Lyman-$β$ observations. arXiv (Cornell University). 7 indexed citations

20.

Sasso, C., V. Andretta, D. Spadaro, & Roberto Susino. (2012). Solar low-lying cool loops and their contribution to the transition region EUV output. Springer Link (Chiba Institute of Technology). 6 indexed citations

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.

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