Roberto Furfaro

4.1k total citations
216 papers, 2.6k citations indexed

About

Roberto Furfaro is a scholar working on Aerospace Engineering, Astronomy and Astrophysics and Artificial Intelligence. According to data from OpenAlex, Roberto Furfaro has authored 216 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Aerospace Engineering, 87 papers in Astronomy and Astrophysics and 27 papers in Artificial Intelligence. Recurrent topics in Roberto Furfaro's work include Astro and Planetary Science (68 papers), Spacecraft Dynamics and Control (52 papers) and Planetary Science and Exploration (45 papers). Roberto Furfaro is often cited by papers focused on Astro and Planetary Science (68 papers), Spacecraft Dynamics and Control (52 papers) and Planetary Science and Exploration (45 papers). Roberto Furfaro collaborates with scholars based in United States, Italy and United Kingdom. Roberto Furfaro's co-authors include Brian Gaudet, Richard Linares, Enrico Schiassi, Richard Linares, Daniel R. Wibben, Mario De Florio, B. D. Ganapol, Andrea Scorsoglio, Daniele Mortari and Andrea D’Ambrosio and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, IEEE Transactions on Geoscience and Remote Sensing and Geology.

In The Last Decade

Roberto Furfaro

194 papers receiving 2.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Roberto Furfaro United States 26 1.4k 805 356 348 276 216 2.6k
Daniele Mortari United States 31 2.5k 1.7× 495 0.6× 572 1.6× 344 1.0× 283 1.0× 153 3.2k
Puneet Singla United States 21 806 0.6× 160 0.2× 639 1.8× 197 0.6× 461 1.7× 173 2.0k
Michèle Lavagna Italy 22 1.6k 1.1× 982 1.2× 192 0.5× 83 0.2× 188 0.7× 230 2.0k
Ryan P. Russell United States 27 1.6k 1.1× 1.3k 1.7× 168 0.5× 155 0.4× 142 0.5× 138 2.3k
Moriba Jah United States 22 1.1k 0.7× 508 0.6× 685 1.9× 64 0.2× 171 0.6× 129 1.6k
Massimiliano Vasile United Kingdom 27 2.2k 1.6× 1.6k 2.0× 333 0.9× 87 0.3× 162 0.6× 313 3.2k
T. Thayaparan Canada 31 1.7k 1.2× 712 0.9× 268 0.8× 22 0.1× 245 0.9× 120 2.8k
Eberhard Gill Netherlands 30 3.6k 2.5× 2.0k 2.5× 254 0.7× 58 0.2× 332 1.2× 226 4.5k
David Vallado United States 13 1.6k 1.1× 1.1k 1.3× 229 0.6× 58 0.2× 94 0.3× 34 2.0k
Yongqiang Cheng China 29 1.6k 1.1× 470 0.6× 205 0.6× 48 0.1× 56 0.2× 206 3.0k

Countries citing papers authored by Roberto Furfaro

Since Specialization
Citations

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

Fields of papers citing papers by Roberto Furfaro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roberto Furfaro

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

All Works

20 of 20 papers shown
1.
D’Ambrosio, Andrea & Roberto Furfaro. (2024). Learning Fuel-Optimal Trajectories for Space Applications via Pontryagin Neural Networks. Aerospace. 11(3). 228–228. 10 indexed citations
2.
Reddy, V., Juan A. Sanchez, P. W. Chodas, et al.. (2024). Challenges in Identifying Artificial Objects in the Near-Earth Object Population: Spectral Characterization of 2020 SO. The Planetary Science Journal. 5(4). 96–96. 4 indexed citations
3.
Federici, Lorenzo, Andrea Scorsoglio, Alessandro Zavoli, & Roberto Furfaro. (2023). Autonomous Guidance Between Quasiperiodic Orbits in Cislunar Space via Deep Reinforcement Learning. Journal of Spacecraft and Rockets. 60(6). 1954–1965. 6 indexed citations
4.
Chesley, Steven R., et al.. (2023). Physical Characterization of Moon Impactor WE0913A. The Planetary Science Journal. 4(11). 217–217. 2 indexed citations
5.
Gaudet, Brian, Richard Linares, & Roberto Furfaro. (2020). Adaptive guidance and integrated navigation with reinforcement meta-learning. Acta Astronautica. 169. 180–190. 67 indexed citations
6.
Gaudet, Brian, Richard Linares, & Roberto Furfaro. (2020). Terminal adaptive guidance via reinforcement meta-learning: Applications to autonomous asteroid close-proximity operations. Acta Astronautica. 171. 1–13. 58 indexed citations
7.
Gaudet, Brian, Richard Linares, & Roberto Furfaro. (2020). Six degree-of-freedom body-fixed hovering over unmapped asteroids via LIDAR altimetry and reinforcement meta-learning. Acta Astronautica. 172. 90–99. 34 indexed citations
8.
Furfaro, Roberto, Richard Linares, Francesco Topputo, et al.. (2020). Modeling irregular small bodies gravity field via extreme learning machines and Bayesian optimization. Advances in Space Research. 67(1). 617–638. 15 indexed citations
9.
Furfaro, Roberto, Kristofer Drozd, & Daniele Mortari. (2019). Energy-optimal rendezvous spacecraft guidance via theory of functional connections. 1 indexed citations
10.
Furfaro, Roberto, et al.. (2019). Space Debris Identification and Characterization via Deep Meta-Learning. 2109. 6123. 6 indexed citations
11.
Furfaro, Roberto, et al.. (2019). Characterizing LEO Objects using Simultaneous Multi-Color Optical Array. Advanced Maui Optical and Space Surveillance Technologies Conference. 51. 1 indexed citations
12.
Furfaro, Roberto, et al.. (2018). Space Objects Classification via Light-Curve Measurements: Deep Convolutional Neural Networks and Model-based Transfer Learning. 11. 17 indexed citations
13.
Furfaro, Roberto, et al.. (2016). Resident Space Object Characterization and Behavior Understanding via Machine Learning and Ontology-based Bayesian Networks. Advanced Maui Optical and Space Surveillance Technologies Conference. 35. 14 indexed citations
14.
Furfaro, Roberto, et al.. (2010). Application of Artificial Neural Network to Infer Subcriticality Level through Kinetic Models. PORTO Publications Open Repository TOrino (Politecnico di Torino). 1 indexed citations
15.
Furfaro, Roberto, et al.. (2009). Subcriticality Determination by Neural-Based Inversion of Space-Energy Neutron Kinetic Equations. PORTO Publications Open Repository TOrino (Politecnico di Torino). 4 indexed citations
16.
Ganapol, B. D., et al.. (2008). Optimization of the Extrapolated Iterative Method for the Multislab Transport Problem. PORTO Publications Open Repository TOrino (Politecnico di Torino). 1 indexed citations
17.
Kargel, Jeffrey S., Roberto Furfaro, Martin Hoelzle, et al.. (2008). Glaciers along the Copper River, Alaska, Controlled by Landslides, Vegetation, Lakes, Rivers (and Climate). AGUFM. 2008.
18.
Ganapol, B. D., et al.. (2008). Accelerated Quasi-Static Method For Neutron Kinetics. Transactions of the American Nuclear Society. 99. 335–337. 1 indexed citations
19.
Furfaro, Roberto, et al.. (2007). Extrapolated iterative solution of the transport equation in inhomogeneous media. PORTO Publications Open Repository TOrino (Politecnico di Torino). 97. 627–629. 1 indexed citations
20.
Furfaro, Roberto, Robert D. Morris, Athanasios Kottas, Matthew A. Taddy, & B. D. Ganapol. (2006). A Gaussian Process Approach to Quantifying the Uncertainty of Vegetation Parameters from Remote Sensing Observations. AGUFM. 2006. 8 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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