Roberto Corizzo
Impact in
- Artificial Intelligence top 5%
- Anomaly Detection Techniques and Applications
- Solar Radiation and Photovoltaics
- Data Stream Mining Techniques
Papers in
-
- Anomaly Detection Techniques and Applications 20
- Data Stream Mining Techniques 13
- Topic Modeling 6
- Solar Radiation and Photovoltaics 5
-
- Time Series Analysis and Forecasting 11
- Co-authors
- Michelangelo Ceci (17 shared papers)Nathalie Japkowicz (26 shared papers)Eftim Zdravevski (9 shared papers)Donato Malerba (8 shared papers)Petre Lameski (6 shared papers)Aleksandra Rashkovska (3 shared papers)Colin Bellinger (5 shared papers)Bartosz Krawczyk (2 shared papers)
- Journals
- Machine Learning (5 papers)Applied Sciences (2 papers)Information Sciences (2 papers)IEEE Access (2 papers)Journal of Intelligent Information Systems (2 papers)
- Partner nations
- United StatesItalyPoland
In The Last Decade
Roberto Corizzo
60 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 122
- Artificial Intelligence 470
- Computational Mathematics 7
- Environmental Engineering 165
- Signal Processing 119
- Media Technology 86
Countries citing papers authored by Roberto Corizzo
This map shows the geographic impact of Roberto Corizzo'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 Corizzo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto Corizzo more than expected).
Fields of papers citing papers by Roberto Corizzo
This network shows the impact of papers produced by Roberto Corizzo. 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 Corizzo. The network helps show where Roberto Corizzo may publish in the future.
Co-authors
The 25 scholars most cited alongside Roberto Corizzo, 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 64 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 125 | |
| 2 | 2020 | 85 | |
| 3 | 2020 | 82 | |
| 4 | 2016 | 69 | |
| 5 | 2020 | 60 | |
| 6 | 2019 | 53 | |
| 7 | 2020 | 42 | |
| 8 | 2019 | 40 | |
| 9 | 2019 | 38 | |
| 10 | 2020 | 37 | |
| 11 | 2020 | 37 | |
| 12 | 2021 | 31 | |
| 13 | 2018 | 29 | |
| 14 | 2023 | 20 | |
| 15 | 2021 | 20 | |
| 16 | 2020 | 19 | |
| 17 | 2020 | 19 | |
| 18 | 2014 | 17 | |
| 19 | 2020 | 16 | |
| 20 | 2021 | 16 |
About Roberto Corizzo
Roberto Corizzo is a scholar working on Artificial Intelligence, Signal Processing, Electrical and Electronic Engineering, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 64 papers that have together received 1.0k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (20 papers), Data Stream Mining Techniques (13 papers), Time Series Analysis and Forecasting (11 papers), Energy Load and Power Forecasting (9 papers), Network Security and Intrusion Detection (9 papers), Topic Modeling (6 papers), Solar Radiation and Photovoltaics (5 papers) and Air Quality Monitoring and Forecasting (4 papers). The work is most often cited by research in Artificial Intelligence (470 citations), Computational Mathematics (7 citations), Environmental Engineering (165 citations), Signal Processing (119 citations) and Media Technology (86 citations). Roberto Corizzo has collaborated with scholars based in United States, Italy and Poland. Frequent co-authors include Michelangelo Ceci, Nathalie Japkowicz, Eftim Zdravevski, Donato Malerba, Petre Lameski, Aleksandra Rashkovska, Colin Bellinger, Bartosz Krawczyk, Kushankur Ghosh and Paula Branco. Their work appears in journals such as Machine Learning, Applied Sciences, Information Sciences, IEEE Access and Journal of Intelligent Information 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.