Mauro Castelli
- Artificial Intelligence top 0.5%
- Molecular Biology top 10%
- Computer Vision and Pattern Recognition top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Environmental Engineering top 5%
- Co-authors
- Leonardo VanneschiIbrahem KandelAleš PopovičSara SilvaLuca ManzoniRay HackneyRana TassabehjiAndrea Delpino
- Topics
- Evolutionary Algorithms and Applications (71 papers)Metaheuristic Optimization Algorithms Research (63 papers)Advanced Multi-Objective Optimization Algorithms (15 papers)
In The Last Decade
Mauro Castelli
196 papers receiving 4.1k citations
Hit Papers
Peers
Comparison fields: 5 of 211
- Artificial Intelligence 1.5k
- Molecular Biology 704
- Computer Vision and Pattern Recognition 457
- Radiology, Nuclear Medicine and Imaging 398
- Environmental Engineering 282
Countries citing papers authored by Mauro Castelli
This map shows the geographic impact of Mauro Castelli'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 Mauro Castelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mauro Castelli more than expected).
Fields of papers citing papers by Mauro Castelli
This network shows the impact of papers produced by Mauro Castelli. 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 Mauro Castelli. The network helps show where Mauro Castelli may publish in the future.
Co-authorship network of co-authors of Mauro Castelli
This figure shows the co-authorship network connecting the top 25 collaborators of Mauro Castelli. A scholar is included among the top collaborators of Mauro Castelli based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mauro Castelli. Mauro Castelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 8 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 9 | |
| 9 | 13 | |
| 10 | 38 | |
| 11 | 17 | |
| 12 | 179 | |
| 13 | 16 | |
| 14 | 5 | |
| 15 | 2 | |
| 16 | 1 | |
| 17 | 32 | |
| 18 | 13 | |
| 19 | 0 | |
| 20 | Better GP benchmarks: community survey results and proposals | 6 |
About Mauro Castelli
Mauro Castelli is a scholar working on Artificial Intelligence, Health Informatics and Computational Theory and Mathematics, having authored 205 papers that have together received 4.3k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (71 papers), Metaheuristic Optimization Algorithms Research (63 papers) and Advanced Multi-Objective Optimization Algorithms (15 papers). The work is most often cited by research in Health Informatics (71 citations), Artificial Intelligence (1.5k citations) and Management Information Systems (266 citations). Mauro Castelli has collaborated with scholars based in Portugal, Italy and Slovenia. Frequent co-authors include Leonardo Vanneschi, Ibrahem Kandel, Aleš Popovič, Sara Silva, Luca Manzoni, Ray Hackney, Rana Tassabehji, Andrea Delpino, Leonardo Trujillo and Illya Bakurov. Their work appears in journals such as PLoS ONE, Scientific Reports and Journal of Business Research.
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.