Ivan Donadello

590 total citations
22 papers, 261 citations indexed

About

Ivan Donadello is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Management Information Systems. According to data from OpenAlex, Ivan Donadello has authored 22 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Management Information Systems. Recurrent topics in Ivan Donadello's work include Explainable Artificial Intelligence (XAI) (6 papers), Topic Modeling (5 papers) and Business Process Modeling and Analysis (3 papers). Ivan Donadello is often cited by papers focused on Explainable Artificial Intelligence (XAI) (6 papers), Topic Modeling (5 papers) and Business Process Modeling and Analysis (3 papers). Ivan Donadello collaborates with scholars based in Italy, United Kingdom and France. Ivan Donadello's co-authors include Mauro Dragoni, Claudio Eccher, Luciano Serafini, Erik Cambria, Artur d’Avila Garcez, Natalia Díaz-Rodríguez, A. Lamas, Siham Tabik, David Filliat and Gianni Franchi and has published in prestigious journals such as ACM Computing Surveys, Frontiers in Psychology and Educational and Psychological Measurement.

In The Last Decade

Ivan Donadello

18 papers receiving 254 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ivan Donadello Italy 10 181 32 28 19 17 22 261
Samuel Jenkins United States 2 184 1.0× 24 0.8× 39 1.4× 18 0.9× 13 0.8× 2 267
Harsha Nori United States 6 224 1.2× 31 1.0× 48 1.7× 27 1.4× 16 0.9× 12 347
Yu-Liang Chou Taiwan 5 157 0.9× 18 0.6× 34 1.2× 16 0.8× 21 1.2× 16 253
Christopher Akiki Germany 4 133 0.7× 21 0.7× 25 0.9× 14 0.7× 8 0.5× 10 201
Nouha Dziri United States 7 252 1.4× 64 2.0× 11 0.4× 17 0.9× 7 0.4× 17 310
Surabhi Adhikari India 10 142 0.8× 20 0.6× 42 1.5× 49 2.6× 22 1.3× 13 299
Bettina Finzel Germany 6 189 1.0× 25 0.8× 49 1.8× 8 0.4× 8 0.5× 14 266
Md Mehrab Tanjim United States 5 135 0.7× 22 0.7× 21 0.8× 79 4.2× 26 1.5× 8 232
Lennart Heim Canada 5 79 0.4× 18 0.6× 10 0.4× 10 0.5× 7 0.4× 8 199
Mehrnoosh Sameki United States 6 126 0.7× 81 2.5× 24 0.9× 17 0.9× 11 0.6× 14 263

Countries citing papers authored by Ivan Donadello

Since Specialization
Citations

This map shows the geographic impact of Ivan Donadello'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 Ivan Donadello with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Donadello more than expected).

Fields of papers citing papers by Ivan Donadello

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ivan Donadello. 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 Ivan Donadello. The network helps show where Ivan Donadello may publish in the future.

Co-authorship network of co-authors of Ivan Donadello

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Donadello. A scholar is included among the top collaborators of Ivan Donadello 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 Ivan Donadello. Ivan Donadello 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.
Francescomarino, Chiara Di, et al.. (2025). Business Process Deviance Mining with Sequential and Declarative Patterns. Business & Information Systems Engineering. 67(6). 877–894.
2.
Francescomarino, Chiara Di, et al.. (2025). Guiding the generation of counterfactual explanations through temporal background knowledge for predictive process monitoring. Data Mining and Knowledge Discovery. 39(5).
3.
Bennetot, Adrien, Ivan Donadello, Mauro Dragoni, et al.. (2024). A Practical Tutorial on Explainable AI Techniques. ACM Computing Surveys. 57(2). 1–44. 29 indexed citations
4.
Dragoni, Mauro, et al.. (2023). Integrating Functional Status Information into Knowledge Graphs to Support Self-Health Management. Data Intelligence. 5(3). 636–662. 2 indexed citations
5.
Donadello, Ivan, et al.. (2023). Outcome-Oriented Prescriptive Process Monitoring based on Temporal Logic Patterns. Engineering Applications of Artificial Intelligence. 126. 106899–106899. 9 indexed citations
6.
Díaz-Rodríguez, Natalia, A. Lamas, Gianni Franchi, et al.. (2022). EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: The MonuMAI cultural heritage use case. arXiv (Cornell University). 62 indexed citations
7.
Donadello, Ivan, Anthony Hunter, Stefano Teso, & Mauro Dragoni. (2022). Machine Learning for Utility Prediction in Argument-Based Computational Persuasion. Proceedings of the AAAI Conference on Artificial Intelligence. 36(5). 5592–5599. 6 indexed citations
8.
Donadello, Ivan & Mauro Dragoni. (2022). AI-enabled persuasive personal health assistant. Social Network Analysis and Mining. 12(1). 5 indexed citations
9.
Dragoni, Mauro, Ivan Donadello, & Erik Cambria. (2022). OntoSenticNet 2: Enhancing Reasoning Within Sentiment Analysis. IEEE Intelligent Systems. 37(2). 103–110. 37 indexed citations
10.
Bennetot, Adrien, Ivan Donadello, Mauro Dragoni, et al.. (2022). A Practical Guide on Explainable Ai Techniques Applied on Biomedical Use Case Applications. SSRN Electronic Journal. 5 indexed citations
11.
Bassi, Giulia, Ivan Donadello, Silvia Gabrielli, et al.. (2021). Early Development of a Virtual Coach for Healthy Coping Interventions in Type 2 Diabetes Mellitus: Validation Study. JMIR Formative Research. 6(2). e27500–e27500.
12.
Dragoni, Mauro, Ivan Donadello, & Claudio Eccher. (2020). Explainable AI meets persuasiveness: Translating reasoning results into behavioral change advice. Artificial Intelligence in Medicine. 105. 101840–101840. 39 indexed citations
13.
Donadello, Ivan, Mauro Dragoni, & Claudio Eccher. (2020). Explaining reasoning algorithms with persuasiveness. View. 646–653. 4 indexed citations
14.
Donadello, Ivan & Mauro Dragoni. (2020). SeXAI: Introducing Concepts into Black Boxes for Explainable Artificial Intelligence.. View. 41–54. 1 indexed citations
15.
Donadello, Ivan & Luciano Serafini. (2019). Compensating Supervision Incompleteness with Prior Knowledge in Semantic Image Interpretation. View. 1–8. 9 indexed citations
16.
Spoto, Andrea, et al.. (2018). New Perspectives in the Adaptive Assessment of Depression: The ATS-PD Version of the QuEDS. Frontiers in Psychology. 9. 1101–1101. 4 indexed citations
17.
Serafini, Luciano, Ivan Donadello, & Artur d’Avila Garcez. (2017). Learning and reasoning in logic tensor networks. View. 125–130. 18 indexed citations
18.
Donadello, Ivan & Luciano Serafini. (2016). Integration of numeric and symbolic information for semantic image interpretation. View. 10(1). 33–47. 9 indexed citations
19.
Donadello, Ivan, et al.. (2016). ATS-PD: An Adaptive Testing System for Psychological Disorders. Educational and Psychological Measurement. 77(5). 792–815. 11 indexed citations
20.
Donadello, Ivan. (2015). Ontology Based Semantic Image Interpretation.. View. 19–24. 1 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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2026