Sergio Spanò
Impact in
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Neural Networks and Applications
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- Distributed Control Multi-Agent Systems
Papers in
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- Blind Source Separation Techniques 3
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- Reinforcement Learning in Robotics 6
- Evolutionary Algorithms and Applications 6
- Neural Networks and Applications 4
- Metaheuristic Optimization Algorithms Research 3
- Co-authors
- G.C. CardarilliLuca Di NunzioM. ReRocco FazzolariDaniele GiardinoLorenzo CaneseAlberto NannarelliFabrizio Silvestri
In The Last Decade
Sergio Spanò
30 papers receiving 530 citations
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 189
- Computer Networks and Communications 107
- Hardware and Architecture 29
- Computer Vision and Pattern Recognition 77
- Control and Systems Engineering 78
Countries citing papers authored by Sergio Spanò
This map shows the geographic impact of Sergio Spanò'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 Sergio Spanò with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergio Spanò more than expected).
Fields of papers citing papers by Sergio Spanò
This network shows the impact of papers produced by Sergio Spanò. 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 Sergio Spanò. The network helps show where Sergio Spanò may publish in the future.
Co-authorship network
The 19 scholars most cited alongside Sergio Spanò, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 9 | |
| 4 | 2024 | 8 | |
| 5 | 2024 | 4 | |
| 6 | 2024 | 11 | |
| 7 | 2023 | 16 | |
| 8 | 2023 | 2 | |
| 9 | 2022 | 9 | |
| 10 | 2021 | 0 | |
| 11 | 2021 | 0 | |
| 12 | 2020 | 11 | |
| 13 | 2020 | 6 | |
| 14 | 2019 | 24 | |
| 15 | 2019 | 23 | |
| 16 | 2019 | 71 | |
| 17 | 2019 | 18 | |
| 18 | 2019 | 1 | |
| 19 | 2019 | 6 | |
| 20 | 2019 | 22 |
About Sergio Spanò
Sergio Spanò is a scholar working on Signal Processing, Artificial Intelligence, Hardware and Architecture, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 34 papers that have together received 550 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (6 papers), Evolutionary Algorithms and Applications (6 papers), Neural Networks and Applications (4 papers), Advanced Adaptive Filtering Techniques (3 papers), Advanced Power Amplifier Design (3 papers), Blind Source Separation Techniques (3 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Advanced Memory and Neural Computing (2 papers). The work is most often cited by research in Artificial Intelligence (189 citations), Computer Networks and Communications (107 citations), Hardware and Architecture (29 citations), Computer Vision and Pattern Recognition (77 citations) and Control and Systems Engineering (78 citations). Sergio Spanò has collaborated with scholars based in Italy and Denmark. Frequent co-authors include G.C. Cardarilli, Luca Di Nunzio, M. Re, Rocco Fazzolari, Daniele Giardino, Lorenzo Canese, Alberto Nannarelli, Fabrizio Silvestri, Massimo Panella and Andrea Ricci. Their work appears in journals such as IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Access, Scientific Reports, Computers & Electrical Engineering 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.