Michelangelo Ceci

3.3k total citations
119 papers, 1.7k citations indexed

About

Michelangelo Ceci is a scholar working on Artificial Intelligence, Signal Processing and Information Systems. According to data from OpenAlex, Michelangelo Ceci has authored 119 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Artificial Intelligence, 28 papers in Signal Processing and 27 papers in Information Systems. Recurrent topics in Michelangelo Ceci's work include Data Mining Algorithms and Applications (23 papers), Rough Sets and Fuzzy Logic (16 papers) and Data Management and Algorithms (14 papers). Michelangelo Ceci is often cited by papers focused on Data Mining Algorithms and Applications (23 papers), Rough Sets and Fuzzy Logic (16 papers) and Data Management and Algorithms (14 papers). Michelangelo Ceci collaborates with scholars based in Italy, Slovenia and United States. Michelangelo Ceci's 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 and has published in prestigious journals such as Bioinformatics, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Michelangelo Ceci

108 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michelangelo Ceci Italy 27 875 321 304 219 199 119 1.7k
Zili Zhang China 27 868 1.0× 270 0.8× 215 0.7× 119 0.5× 381 1.9× 119 2.0k
Naoki Abe Japan 26 1.8k 2.0× 335 1.0× 330 1.1× 209 1.0× 235 1.2× 100 2.9k
Jesús Ariel Carrasco-Ochoa Mexico 22 1.3k 1.4× 460 1.4× 135 0.4× 182 0.8× 495 2.5× 110 2.2k
Stefan Wrobel Germany 23 901 1.0× 353 1.1× 171 0.6× 373 1.7× 597 3.0× 76 2.2k
Marco Lippi Italy 21 782 0.9× 232 0.7× 169 0.6× 143 0.7× 165 0.8× 75 2.2k
Hae-Sang Park South Korea 4 520 0.6× 171 0.5× 104 0.3× 199 0.9× 244 1.2× 5 1.4k
José Fco. Martínez-Trinidad Mexico 24 1.3k 1.5× 484 1.5× 139 0.5× 199 0.9× 524 2.6× 116 2.3k
Fei Hao China 26 853 1.0× 534 1.7× 141 0.5× 146 0.7× 258 1.3× 167 2.2k
Guojun Gan United States 19 1.2k 1.4× 274 0.9× 108 0.4× 284 1.3× 578 2.9× 64 2.5k
Niall M. Adams United Kingdom 25 1.7k 2.0× 339 1.1× 118 0.4× 307 1.4× 288 1.4× 105 2.8k

Countries citing papers authored by Michelangelo Ceci

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Pio, Gianvito, et al.. (2025). Handling complex backgrounds and light perturbations for enhancing learning tasks from images of vegetables. Journal of Intelligent Information Systems. 64(1). 215–238.
2.
Ceci, Michelangelo, et al.. (2025). An end-to-end explainability framework for spatio-temporal predictive modeling. Machine Learning. 114(4). 1 indexed citations
3.
Ceci, Michelangelo, et al.. (2025). Positional trace encoding for next activity prediction in event logs. Knowledge-Based Systems. 319. 113544–113544.
5.
Ceci, Michelangelo, Sergio Flesca, Giuseppe Manco, & Elio Masciari. (2024). Special issue on intelligent systems. Journal of Intelligent Information Systems. 62(4). 883–886.
6.
Ceci, Michelangelo, et al.. (2024). Semi-Supervised Predictive Clustering Trees for (Hierarchical) Multi-Label Classification. International Journal of Intelligent Systems. 2024. 1–21. 3 indexed citations
7.
Petković, Matej, Michelangelo Ceci, Gianvito Pio, et al.. (2022). Relational tree ensembles and feature rankings. Knowledge-Based Systems. 251. 109254–109254. 4 indexed citations
8.
Pio, Gianvito, et al.. (2022). Distributed Heterogeneous Transfer Learning for Link Prediction in the Positive Unlabeled Setting. 2022 IEEE International Conference on Big Data (Big Data). 5 indexed citations
9.
Hess, Sibylle, Gianvito Pio, Michiel E. Hochstenbach, & Michelangelo Ceci. (2021). BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent. Data Mining and Knowledge Discovery. 35(6). 2542–2576. 8 indexed citations
10.
Corizzo, Roberto, Michelangelo Ceci, Hadi Fanaee‐T, & João Gama. (2020). Multi-aspect renewable energy forecasting. Information Sciences. 546. 701–722. 60 indexed citations
11.
Pio, Gianvito, et al.. (2019). Exploiting causality in gene network reconstruction based on graph embedding. Machine Learning. 109(6). 1231–1279. 25 indexed citations
12.
Soldatova, Larisa, Joaquin Vanschoren, Michelangelo Ceci, & George Α. Papadopoulos. (2018). Discovery science : 21st International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings. Data Archiving and Networked Services (DANS). 11198. 1 indexed citations
13.
Pio, Gianvito, Michelangelo Ceci, Domenica D’Elia, & Donato Malerba. (2014). Learning to Combine miRNA Target Predictions: a Semi-supervised Ensemble Learning Approach.. SEBD. 21–28. 1 indexed citations
14.
Ceci, Michelangelo, et al.. (2014). Big Data Techniques For Renewable Energy Market.. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 369–377. 5 indexed citations
15.
Pio, Gianvito, Michelangelo Ceci, Domenica D’Elia, Corrado Appice Annalisa Malerba Donato Loglisci, & Donato Malerba. (2013). HOCCLUS2: A Biclustering Algorithm for the Discovery of miRNA: mRNA regulatory modules.. SEBD. 445–452. 1 indexed citations
16.
Ceci, Michelangelo, Alfredo Cuzzocrea, & Donato Malerba. (2011). Supporting Roll-Up and Drill-Down Operations over OLAP Data Cubes with Continuous Dimensions via Density-Based Hierarchical Clustering.. ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/). 57–65. 4 indexed citations
17.
Ceci, Michelangelo, Margherita Berardi, & Donato Malerba. (2007). RELATIONAL DATA MINING AND ILP FOR DOCUMENT IMAGE UNDERSTANDING. Applied Artificial Intelligence. 21(4-5). 317–342. 7 indexed citations
18.
Ceci, Michelangelo, et al.. (2007). Transductive Learning from Relational Data. Lecture notes in computer science. 324–338. 2 indexed citations
19.
Berardi, Margherita, Michelangelo Ceci, Floriana Esposito, & Donato Malerba. (2003). Learning logic programs for layout analysis correction. International Conference on Machine Learning. 27–34. 2 indexed citations
20.
Appice, Annalisa, Michelangelo Ceci, & Donato Malerba. (2002). KDB2000: An integrated knowledge discovery tool. WIT transactions on information and communication technologies. 28. 531–540. 3 indexed citations

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.

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