Sergio Spanò
Impact in
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Neural Networks and Applications
- Hardware and Architecture top 10%
Papers in
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- Evolutionary Algorithms and Applications 9
- Reinforcement Learning in Robotics 8
- Neural Networks and Applications 6
- Metaheuristic Optimization Algorithms Research 4
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- Advanced Memory and Neural Computing 4
- CCD and CMOS Imaging Sensors 4
- Co-authors
- G.C. Cardarilli (40 shared papers)Luca Di Nunzio (37 shared papers)M. Re (40 shared papers)Rocco Fazzolari (33 shared papers)Daniele Giardino (27 shared papers)Lorenzo Canese (14 shared papers)Alberto Nannarelli (10 shared papers)Fabrizio Silvestri (1 shared paper)
In The Last Decade
Sergio Spanò
40 papers receiving 655 citations
Sergio Spanò's Hit Papers
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 234
- Hardware and Architecture 39
- Computer Networks and Communications 124
- Computer Vision and Pattern Recognition 87
- Control and Systems Engineering 92
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-authors
The 20 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
Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Multi-Agent Reinforcement Learning: A Review of Challenges and Applications Hit paper breakdown → | 2021 | 218 |
| 2 | 2019 | 81 | |
| 3 | 2021 | 67 | |
| 4 | 2019 | 26 | |
| 5 | 2019 | 26 | |
| 6 | 2019 | 24 | |
| 7 | 2019 | 21 | |
| 8 | 2018 | 18 | |
| 9 | 2019 | 16 | |
| 10 | 2019 | 16 | |
| 11 | 2023 | 16 | |
| 12 | 2022 | 13 | |
| 13 | 2019 | 12 | |
| 14 | 2024 | 11 | |
| 15 | 2020 | 11 | |
| 16 | 2024 | 11 | |
| 17 | 2024 | 11 | |
| 18 | 2022 | 9 | |
| 19 | 2020 | 8 | |
| 20 | 2021 | 7 |
About Sergio Spanò
Sergio Spanò is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Signal Processing, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 46 papers that have together received 675 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (9 papers), Reinforcement Learning in Robotics (8 papers), Neural Networks and Applications (6 papers), Advanced Memory and Neural Computing (4 papers), Advanced Adaptive Filtering Techniques (4 papers), Digital Filter Design and Implementation (4 papers), Metaheuristic Optimization Algorithms Research (4 papers) and CCD and CMOS Imaging Sensors (4 papers). The work is most often cited by research in Artificial Intelligence (234 citations), Hardware and Architecture (39 citations), Computer Networks and Communications (124 citations), Computer Vision and Pattern Recognition (87 citations) and Control and Systems Engineering (92 citations). Sergio Spanò has collaborated with scholars based in Italy, Denmark and India. Frequent co-authors include G.C. Cardarilli, Luca Di Nunzio, M. Re, Rocco Fazzolari, Daniele Giardino, Lorenzo Canese, Alberto Nannarelli, Fabrizio Silvestri, Andrea Ricci and Massimo Panella. Their work appears in journals such as IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Access, Scientific Reports, Sensors and Computers & Electrical Engineering.
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.