Davide Guzzetti

581 citations
33 papers · 435 · h-index 12

Impact in

Papers in

Davide Guzzetti

30 papers receiving 419 citations

Peers

Davide Guzzetti
Comparison fields: 5 of 29
  • Aerospace Engineering 303
  • Statistical and Nonlinear Physics 19
  • Computer Vision and Pattern Recognition 33
  • Artificial Intelligence 46
  • Industrial and Manufacturing Engineering 10
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Citations per field
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Citations per year

Countries citing papers authored by Davide Guzzetti

Since Specialization
Citations

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

Fields of papers citing papers by Davide Guzzetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Davide Guzzetti, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Davide Guzzetti Line = papers co-authored together Davide Guzzetti links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202069
2 202244
3 201437
4 202136
5 201631
6 201528
7 201628
8
Orbit Maintenance and Navigation of Human Spacecraft at Cislunar Near Rectilinear Halo Orbits
201724
9 202123
10 201415
11 201914
12 201813
13 201811
14 202111
15 201410
16 20199
17
Large space structures dynamics in a multibody gravitational environment
20125
18
Deep Reinforcement Learning to Enhance Fly-Around Guidance for Uncooperative Space Objects Smart Imaging
20205
19 20194
20 20234

About Davide Guzzetti

Davide Guzzetti is a scholar working on Aerospace Engineering, Civil and Structural Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition and Industrial and Manufacturing Engineering, having authored 33 papers that have together received 435 indexed citations. Recurring topics across this work include Spacecraft Dynamics and Control (22 papers), Space Satellite Systems and Control (6 papers), Reinforcement Learning in Robotics (4 papers), Structural Analysis and Optimization (4 papers), Satellite Communication Systems (2 papers), Advanced Materials and Mechanics (2 papers), Polymer composites and self-healing (1 paper) and Machine Learning in Materials Science (1 paper). The work is most often cited by research in Aerospace Engineering (303 citations), Statistical and Nonlinear Physics (19 citations), Computer Vision and Pattern Recognition (33 citations), Artificial Intelligence (46 citations) and Industrial and Manufacturing Engineering (10 citations). Davide Guzzetti has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Kathleen Connor Howell, Vinamra Agrawal, Michèle Roberta Lavagna, Natasha Bosanac, Xiangyuan Zeng, Yuyang You, David C. Folta, Hexi BAOYIN, Rohan Sood and Loïc Chappaz. Their work appears in journals such as Acta Astronautica, The Journal of the Astronautical Sciences, Journal of Guidance Control and Dynamics, Science China Technological Sciences and IEEE Transactions on Aerospace and Electronic Systems.

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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