Ivan Zyrianoff
Impact in
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- IoT and Edge/Fog Computing
- Caching and Content Delivery
- Information Systems top 10%
- Blockchain Technology Applications and Security
- Cloud Computing and Resource Management
Papers in
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- IoT and Edge/Fog Computing 25
- Software System Performance and Reliability 4
- Caching and Content Delivery 4
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- Context-Aware Activity Recognition Systems 11
- Co-authors
- Carlos Kamienski (24 shared papers)Marco Di Felice (25 shared papers)Federico Montori (11 shared papers)Tullio Salmon Cinotti (5 shared papers)João Henrique Kleinschmidt (6 shared papers)Juha-Pekka Soininen (3 shared papers)Luca Sciullo (11 shared papers)Lorenzo Gigli (15 shared papers)
In The Last Decade
Ivan Zyrianoff
37 papers receiving 369 citations
Peers
Comparison fields: 5 of 60
- Computer Networks and Communications 210
- Information Systems 76
- Computer Vision and Pattern Recognition 64
- Media Technology 19
- Water Science and Technology 29
Countries citing papers authored by Ivan Zyrianoff
This map shows the geographic impact of Ivan Zyrianoff'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 Ivan Zyrianoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Zyrianoff more than expected).
Fields of papers citing papers by Ivan Zyrianoff
This network shows the impact of papers produced by Ivan Zyrianoff. 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 Ivan Zyrianoff. The network helps show where Ivan Zyrianoff may publish in the future.
Co-authors
The 25 scholars most cited alongside Ivan Zyrianoff, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 56 | |
| 2 | 2017 | 36 | |
| 3 | 2018 | 31 | |
| 4 | 2015 | 24 | |
| 5 | 2023 | 23 | |
| 6 | 2018 | 21 | |
| 7 | 2020 | 21 | |
| 8 | 2022 | 18 | |
| 9 | 2024 | 15 | |
| 10 | 2020 | 12 | |
| 11 | 2023 | 11 | |
| 12 | 2021 | 11 | |
| 13 | 2022 | 10 | |
| 14 | 2022 | 10 | |
| 15 | 2020 | 10 | |
| 16 | 2023 | 9 | |
| 17 | 2024 | 7 | |
| 18 | 2018 | 5 | |
| 19 | 2021 | 5 | |
| 20 | 2021 | 5 |
About Ivan Zyrianoff
Ivan Zyrianoff is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Information Systems and Plant Science, having authored 42 papers that have together received 377 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (25 papers), Context-Aware Activity Recognition Systems (11 papers), IoT Networks and Protocols (7 papers), Software System Performance and Reliability (4 papers), Blockchain Technology Applications and Security (4 papers), Cloud Computing and Resource Management (4 papers), Smart Agriculture and AI (4 papers) and Caching and Content Delivery (4 papers). The work is most often cited by research in Computer Networks and Communications (210 citations), Information Systems (76 citations), Computer Vision and Pattern Recognition (64 citations), Media Technology (19 citations) and Water Science and Technology (29 citations). Ivan Zyrianoff has collaborated with scholars based in Italy, Brazil and Finland. Frequent co-authors include Carlos Kamienski, Marco Di Felice, Federico Montori, Tullio Salmon Cinotti, João Henrique Kleinschmidt, Juha-Pekka Soininen, Luca Sciullo, Lorenzo Gigli, Luca Roffia and Marc Jentsch. Their work appears in journals such as IEEE Access, IEEE Internet of Things Journal, Ad Hoc Networks, IEEE Communications Magazine and Sensors.
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.