Federico Quin
Impact in
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- Software Reliability and Analysis Research
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- Software System Performance and Reliability
- Distributed systems and fault tolerance
- IoT and Edge/Fog Computing
Papers in
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- Software System Performance and Reliability 7
- Network Security and Intrusion Detection 1
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- Advanced Software Engineering Methodologies 7
- Machine Learning in Healthcare 1
- Co-authors
- Danny WeynsSam MichielsMatthias GalsterLars GrunskeMarco VieiraIlias GerostathopoulosGabriel A. MorenoBarbora Bühnová
- Journals
- Journal of Systems and Software (2 papers)ACM Transactions on Autonomous and Adaptive Systems (2 papers)arXiv (Cornell University) (1 paper)ACM SIGSOFT Software Engineering Notes (1 paper)Lirias (KU Leuven) (3 papers)
In The Last Decade
Federico Quin
9 papers receiving 204 citations
Peers
Comparison fields: 5 of 59
- Software 20
- Computer Networks and Communications 95
- Artificial Intelligence 121
- Information Systems 66
- Hardware and Architecture 11
Countries citing papers authored by Federico Quin
This map shows the geographic impact of Federico Quin'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 Federico Quin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Federico Quin more than expected).
Fields of papers citing papers by Federico Quin
This network shows the impact of papers produced by Federico Quin. 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 Federico Quin. The network helps show where Federico Quin may publish in the future.
Co-authors
The 19 scholars most cited alongside Federico Quin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 19 | |
| 2 | 2022 | 7 | |
| 3 | 2022 | 4 | |
| 4 | 2022 | 3 | |
| 5 | 2022 | 10 | |
| 6 | 2021 | 26 | |
| 7 | 2020 | 83 | |
| 8 | 2020 | 26 | |
| 9 | 2019 | 33 |
About Federico Quin
Federico Quin is a scholar working on Computer Networks and Communications, Artificial Intelligence, Information Systems, Statistics, Probability and Uncertainty and Statistics and Probability, having authored 9 papers that have together received 211 indexed citations. Recurring topics across this work include Software System Performance and Reliability (7 papers), Advanced Software Engineering Methodologies (7 papers), Software Engineering Research (5 papers), Reliability and Agreement in Measurement (1 paper), Statistical Methods in Clinical Trials (1 paper), Smart Grid Security and Resilience (1 paper), Machine Learning in Healthcare (1 paper) and Network Security and Intrusion Detection (1 paper). The work is most often cited by research in Software (20 citations), Computer Networks and Communications (95 citations), Artificial Intelligence (121 citations), Information Systems (66 citations) and Hardware and Architecture (11 citations). Federico Quin has collaborated with scholars based in Belgium, Sweden and Brazil. Frequent co-authors include Danny Weyns, Sam Michiels, Matthias Galster, Lars Grunske, Marco Vieira, Ilias Gerostathopoulos, Gabriel A. Moreno, Barbora Bühnová, Pooyan Jamshidi and Judith Michael. Their work appears in journals such as Journal of Systems and Software, ACM Transactions on Autonomous and Adaptive Systems, arXiv (Cornell University), ACM SIGSOFT Software Engineering Notes and Lirias (KU Leuven).
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.