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
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- Advanced Software Engineering Methodologies 7
- Machine Learning in Healthcare 1
- Co-authors
- Danny Weyns (9 shared papers)Sam Michiels (2 shared papers)Matthias Galster (1 shared paper)Jonas Van Der Donckt (1 shared paper)Nicolás Cardozo (1 shared paper)Thomas Vogel (1 shared paper)Patrizio Pelliccione (1 shared paper)Bradley Schmerl (1 shared paper)
- Journals
- ACM Transactions on Autonomous and Adaptive Systems (2 papers)Journal of Systems and Software (2 papers)ACM SIGSOFT Software Engineering Notes (1 paper)Lirias (KU Leuven) (3 papers)arXiv (Cornell University) (1 paper)
In The Last Decade
Federico Quin
9 papers receiving 218 citations
Peers
Comparison fields: 5 of 59
- Software 20
- Computer Networks and Communications 96
- Artificial Intelligence 125
- Information Systems 67
- Computer Science Applications 9
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 20 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 | 2020 | 85 | |
| 2 | 2019 | 34 | |
| 3 | 2020 | 27 | |
| 4 | 2024 | 26 | |
| 5 | 2021 | 26 | |
| 6 | 2022 | 10 | |
| 7 | 2022 | 8 | |
| 8 | 2022 | 5 | |
| 9 | 2022 | 3 |
About Federico Quin
Federico Quin is a scholar working on Computer Networks and Communications, Artificial Intelligence, Information Systems, Surgery and Control and Systems Engineering, having authored 9 papers that have together received 224 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), Smart Grid Security and Resilience (1 paper), Healthcare Technology and Patient Monitoring (1 paper), Statistical Methods in Clinical Trials (1 paper), Machine Learning in Healthcare (1 paper) and Reliability and Agreement in Measurement (1 paper). The work is most often cited by research in Software (20 citations), Computer Networks and Communications (96 citations), Artificial Intelligence (125 citations), Information Systems (67 citations) and Computer Science Applications (9 citations). Federico Quin has collaborated with scholars based in Belgium, Sweden and Bolivia. Frequent co-authors include Danny Weyns, Sam Michiels, Matthias Galster, Jonas Van Der Donckt, Nicolás Cardozo, Thomas Vogel, Patrizio Pelliccione, Bradley Schmerl, Marco Vieira and Lars Grunske. Their work appears in journals such as ACM Transactions on Autonomous and Adaptive Systems, Journal of Systems and Software, ACM SIGSOFT Software Engineering Notes, Lirias (KU Leuven) and arXiv (Cornell University).
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.