Alan Perotti

607 total citations
19 papers, 301 citations indexed

About

Alan Perotti is a scholar working on Artificial Intelligence, Health Informatics and Molecular Biology. According to data from OpenAlex, Alan Perotti has authored 19 papers receiving a total of 301 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 4 papers in Health Informatics and 2 papers in Molecular Biology. Recurrent topics in Alan Perotti's work include Explainable Artificial Intelligence (XAI) (8 papers), Machine Learning in Healthcare (5 papers) and Artificial Intelligence in Healthcare and Education (4 papers). Alan Perotti is often cited by papers focused on Explainable Artificial Intelligence (XAI) (8 papers), Machine Learning in Healthcare (5 papers) and Artificial Intelligence in Healthcare and Education (4 papers). Alan Perotti collaborates with scholars based in Italy, United Kingdom and Netherlands. Alan Perotti's co-authors include Cecilia Panigutti, Dino Pedreschi, Paolo Bajardi, Elvio Gilberto Amparore, André Panisson, Salvatore Rinzivillo, Fosca Giannotti, Andrea Beretta, Federica Bisio and Giovanni Petri and has published in prestigious journals such as European Journal of Cancer, Journal of Personalized Medicine and Frontiers in Computational Neuroscience.

In The Last Decade

Alan Perotti

16 papers receiving 287 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Alan Perotti Italy	8	204	74	26	20	20	19	301
Huiqi Deng China	6	178 0.9×	43 0.6×	12 0.5×	31 1.6×	13 0.7×	7	338
Milad Moradi Austria	11	274 1.3×	40 0.5×	13 0.5×	12 0.6×	22 1.1×	17	371
Bettina Finzel Germany	6	189 0.9×	49 0.7×	25 1.0×	10 0.5×	8 0.4×	14	266
Yu-Liang Chou Taiwan	5	157 0.8×	34 0.5×	28 1.1×	5 0.3×	26 1.3×	16	253
Dinesh Kalla United States	7	128 0.6×	92 1.2×	14 0.5×	15 0.8×	36 1.8×	21	280
Jörg Schlötterer Germany	7	228 1.1×	42 0.6×	19 0.7×	11 0.6×	5 0.3×	25	339
David Schneeberger Austria	4	129 0.6×	75 1.0×	35 1.3×	4 0.2×	7 0.3×	5	235
Nigar M. Shafiq Surameery Iraq	5	149 0.7×	129 1.7×	28 1.1×	20 1.0×	12 0.6×	13	301
Andrew Trask United Kingdom	5	262 1.3×	65 0.9×	14 0.5×	18 0.9×	16 0.8×	6	354

Countries citing papers authored by Alan Perotti

Since Specialization

Citations

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

Fields of papers citing papers by Alan Perotti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alan Perotti

This figure shows the co-authorship network connecting the top 25 collaborators of Alan Perotti. A scholar is included among the top collaborators of Alan Perotti 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 Alan Perotti. Alan Perotti is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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19 of 19 papers shown

Panisson, André, et al.. (2025). Beyond Input Attribution: A Hands-On Tutorial to Concept-Based Explainable AI and Mechanistic Interpretability. 6247–6248.

Rattay, Tim, G. Bologna, André Dekker, et al.. (2024). Development of an explainable AI prediction model for arm lymphoedema following breast cancer surgery and radiotherapy. European Journal of Cancer. 200. 113624–113624.

Panisson, André, et al.. (2024). LLM-Generated Class Descriptions for Semantically Meaningful Image Classification. 50–61. 1 indexed citations

Perotti, Alan, et al.. (2024). Auditing Fairness and Explainability in Chest X-Ray Image Classifiers. 1308–1315. 1 indexed citations

Perotti, Alan, et al.. (2023). Machine Learning Model as a Useful Tool for Prediction of Thyroid Nodules Histology, Aggressiveness and Treatment-Related Complications. Journal of Personalized Medicine. 13(11). 1615–1615. 1 indexed citations

Panigutti, Cecilia, Andrea Beretta, Fosca Giannotti, et al.. (2023). Co-design of Human-centered, Explainable AI for Clinical Decision Support. ACM Transactions on Interactive Intelligent Systems. 13(4). 1–35. 43 indexed citations

Celeghin, Alessia, et al.. (2023). Convolutional neural networks for vision neuroscience: significance, developments, and outstanding issues. Frontiers in Computational Neuroscience. 17. 1153572–1153572. 16 indexed citations

Perotti, Alan, Paolo Bajardi, Francesco Bonchi, & André Panisson. (2023). Explaining Identity-aware Graph Classifiers through the Language of Motifs. 1–8. 4 indexed citations

Panigutti, Cecilia, Alan Perotti, André Panisson, Paolo Bajardi, & Dino Pedreschi. (2021). FairLens: Auditing black-box clinical decision support systems. CINECA IRIS Institutial research information system (University of Pisa). 39 indexed citations

10.

Amparore, Elvio Gilberto, et al.. (2021). Forecast of Distributed Energy Generation and Consumption in a Partially Observable Electrical Grid: A Machine Learning Approach. IRIS Research product catalog (Sapienza University of Rome). 1–6. 1 indexed citations

11.

Amparore, Elvio Gilberto, Alan Perotti, & Paolo Bajardi. (2021). To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods. PeerJ Computer Science. 7. e479–e479. 51 indexed citations

12.

Panisson, André, et al.. (2020). Explainability Methods for Natural Language Processing: Applications to Sentiment Analysis.. SEBD. 100–107. 13 indexed citations

13.

Panigutti, Cecilia, Alan Perotti, & Dino Pedreschi. (2020). Doctor XAI. CINECA IRIS Institutial research information system (University of Pisa). 629–639. 97 indexed citations

14.

Krishnakumari, Panchamy, et al.. (2018). Understanding Network Traffic States using Transfer Learning. Research Repository (Delft University of Technology). 1396–1401. 8 indexed citations

15.

Bisio, Federica, et al.. (2017). Real-time behavioral DGA detection through machine learning. 1–6. 21 indexed citations

16.

Perotti, Alan, Artur d’Avila Garcez, & Guido Boella. (2014). Neural Networks for Runtime Verification. 42. 2637–2644.

17.

Boella, Guido, et al.. (2012). Learning and reasoning about norms using neural-symbolic systems. Adaptive Agents and Multi-Agents Systems. 1023–1030. 2 indexed citations

18.

Perotti, Alan, Guido Boella, Dov M. Gabbay, Leendert van der Torre, & Serena Villata. (2011). Conditional Labelling for Abstract Argumentation.. 59–65. 2 indexed citations

19.

Boella, Guido, Dov M. Gabbay, Alan Perotti, & Serena Villata. (2010). Coalition Formation via Negotiation in Multiagent Systems with Voluntary Attacks. Open Repository and Bibliography (University of Luxembourg). 25–32. 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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