Danilo Pelusi
- Artificial Intelligence top 2%
- Fuzzy Logic and Control Systems 11
- Neural Networks and Applications 11
- Anomaly Detection Techniques and Applications 7
- Metaheuristic Optimization Algorithms Research 7
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- Rough Sets and Fuzzy Logic 9
- Signal Processing top 5%
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- Multi-Criteria Decision Making 8
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- Data Mining Algorithms and Applications 6
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- COVID-19 diagnosis using AI 6
- Co-authors
- Janmenjoy NayakBighnaraj NaikYong DengLuca G. TalliniRaffaele MascellaRajesh SinghSuresh Chandra SatapathyPraveen Kumar Malik
- Cited by
- Artificial IntelligenceComputer Networks and CommunicationsComputational Theory and Mathematics
In The Last Decade
Danilo Pelusi
87 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Artificial Intelligence 702
- Computer Networks and Communications 339
- Computational Theory and Mathematics 202
- Signal Processing 135
- Management Science and Operations Research 143
Countries citing papers authored by Danilo Pelusi
This map shows the geographic impact of Danilo Pelusi'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 Danilo Pelusi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danilo Pelusi more than expected).
Fields of papers citing papers by Danilo Pelusi
This network shows the impact of papers produced by Danilo Pelusi. 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 Danilo Pelusi. The network helps show where Danilo Pelusi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Danilo Pelusi, 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 | 4 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 9 | |
| 4 | 2024 | 22 | |
| 5 | 2024 | 20 | |
| 6 | 2024 | 10 | |
| 7 | 2024 | 9 | |
| 8 | 2023 | 0 | |
| 9 | 2023 | 2 | |
| 10 | 2023 | 2 | |
| 11 | 2022 | 10 | |
| 12 | 2021 | 5 | |
| 13 | 2021 | 2 | |
| 14 | 2020 | 18 | |
| 15 | 2019 | 28 | |
| 16 | 2019 | 24 | |
| 17 | 2019 | 11 | |
| 18 | 2019 | 4 | |
| 19 | 2019 | 15 | |
| 20 | 2016 | 20 |
About Danilo Pelusi
Danilo Pelusi is a scholar working on Artificial Intelligence, Health Informatics, Computational Theory and Mathematics, Management Science and Operations Research and Instrumentation, having authored 93 papers that have together received 1.8k indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (11 papers), Neural Networks and Applications (11 papers), Rough Sets and Fuzzy Logic (9 papers), Multi-Criteria Decision Making (8 papers), Anomaly Detection Techniques and Applications (7 papers), Metaheuristic Optimization Algorithms Research (7 papers), Data Mining Algorithms and Applications (6 papers) and COVID-19 diagnosis using AI (6 papers). The work is most often cited by research in Artificial Intelligence (702 citations), Computer Networks and Communications (339 citations), Computational Theory and Mathematics (202 citations), Signal Processing (135 citations) and Management Science and Operations Research (143 citations). Danilo Pelusi has collaborated with scholars based in Italy, India and China. Frequent co-authors include Janmenjoy Nayak, Bighnaraj Naik, Yong Deng, Luca G. Tallini, Raffaele Mascella, Rajesh Singh, Suresh Chandra Satapathy, Praveen Kumar Malik, Weiping Ding and Anita Gehlot. Their work appears in journals such as Mathematical Biosciences & Engineering, Neural Computing and Applications, Engineering Applications of Artificial Intelligence, Expert Systems with Applications and Information Sciences.
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.