Michelangelo Ceci
- Artificial Intelligence top 1%
- Information Systems top 2%
- Molecular Biology
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Donato MalerbaGianvito PioRoberto CorizzoAnnalisa AppiceSašo DžeroskiDomenica D’EliaNathalie JapkowiczDragi Kocev
- Topics
- Data Mining Algorithms and Applications (23 papers)Rough Sets and Fuzzy Logic (16 papers)Data Management and Algorithms (14 papers)
- Partner nations
- ItalySloveniaUnited States
In The Last Decade
Michelangelo Ceci
108 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 140
- Artificial Intelligence 875
- Information Systems 321
- Molecular Biology 304
- Signal Processing 219
- Computer Vision and Pattern Recognition 199
Countries citing papers authored by Michelangelo Ceci
This map shows the geographic impact of Michelangelo Ceci'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 Michelangelo Ceci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michelangelo Ceci more than expected).
Fields of papers citing papers by Michelangelo Ceci
This network shows the impact of papers produced by Michelangelo Ceci. 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 Michelangelo Ceci. The network helps show where Michelangelo Ceci may publish in the future.
Co-authorship network of co-authors of Michelangelo Ceci
This figure shows the co-authorship network connecting the top 25 collaborators of Michelangelo Ceci. A scholar is included among the top collaborators of Michelangelo Ceci 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 Michelangelo Ceci. Michelangelo Ceci is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 4 | |
| 8 | 5 | |
| 9 | 8 | |
| 10 | 60 | |
| 11 | 25 | |
| 12 | 1 | |
| 13 | Learning to Combine miRNA Target Predictions: a Semi-supervised Ensemble Learning Approach. | 1 |
| 14 | Big Data Techniques For Renewable Energy Market. | 5 |
| 15 | HOCCLUS2: A Biclustering Algorithm for the Discovery of miRNA: mRNA regulatory modules. | 1 |
| 16 | Supporting Roll-Up and Drill-Down Operations over OLAP Data Cubes with Continuous Dimensions via Density-Based Hierarchical Clustering. | 4 |
| 17 | 7 | |
| 18 | Transductive Learning from Relational Data | 2 |
| 19 | Learning logic programs for layout analysis correction | 2 |
| 20 | 3 |
About Michelangelo Ceci
Michelangelo Ceci is a scholar working on Signal Processing, Artificial Intelligence and Computational Mathematics, having authored 119 papers that have together received 1.7k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (23 papers), Rough Sets and Fuzzy Logic (16 papers) and Data Management and Algorithms (14 papers). The work is most often cited by research in Artificial Intelligence (875 citations), Signal Processing (219 citations) and Computational Mathematics (11 citations). Michelangelo Ceci has collaborated with scholars based in Italy, Slovenia and United States. Frequent co-authors include Donato Malerba, Gianvito Pio, Roberto Corizzo, Annalisa Appice, Sašo Džeroski, Domenica D’Elia, Nathalie Japkowicz, Dragi Kocev, Jurica Levatić and Fabio Fumarola. Their work appears in journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.