Lerina Aversano

2.6k total citations
118 papers, 1.7k citations indexed

About

Lerina Aversano is a scholar working on Information Systems, Management Information Systems and Artificial Intelligence. According to data from OpenAlex, Lerina Aversano has authored 118 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Information Systems, 35 papers in Management Information Systems and 32 papers in Artificial Intelligence. Recurrent topics in Lerina Aversano's work include Software Engineering Research (42 papers), Service-Oriented Architecture and Web Services (35 papers) and Business Process Modeling and Analysis (29 papers). Lerina Aversano is often cited by papers focused on Software Engineering Research (42 papers), Service-Oriented Architecture and Web Services (35 papers) and Business Process Modeling and Analysis (29 papers). Lerina Aversano collaborates with scholars based in Italy, Spain and United States. Lerina Aversano's co-authors include Massimiliano Di Penta, Luigi Cerulo, Mario Luca Bernardi, Maria Tortorella, Marta Cimitile, Gerardo Canfora, Riccardo Pecori, Martina Iammarino, Suresh Thummalapenta and Andrea De Lucia and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Pattern Recognition.

In The Last Decade

Lerina Aversano

109 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lerina Aversano Italy 23 1.1k 523 509 393 275 118 1.7k
He Jiang China 25 1.3k 1.1× 634 1.2× 618 1.2× 378 1.0× 26 0.1× 161 1.8k
Jieming Zhu China 26 1.8k 1.6× 1.5k 2.8× 602 1.2× 1.9k 4.8× 55 0.2× 79 3.3k
Jianling Sun China 20 924 0.8× 514 1.0× 395 0.8× 366 0.9× 37 0.1× 79 1.4k
Bart Goethals Belgium 23 1.4k 1.3× 847 1.6× 158 0.3× 367 0.9× 33 0.1× 95 2.1k
Weiyi Shang Canada 30 2.0k 1.7× 696 1.3× 1.1k 2.1× 1.7k 4.4× 57 0.2× 117 2.7k
Dietmar Ebner Austria 7 420 0.4× 532 1.0× 52 0.1× 207 0.5× 100 0.4× 12 1.2k
Daya Guo China 11 1.6k 1.4× 1.3k 2.5× 766 1.5× 380 1.0× 31 0.1× 21 2.4k
Abdelwahab Hamou‐Lhadj Canada 23 1.1k 1.0× 623 1.2× 659 1.3× 926 2.4× 42 0.2× 140 1.7k
O. P. Vyas India 17 384 0.3× 498 1.0× 67 0.1× 353 0.9× 30 0.1× 120 1.1k
A. Govardhan India 18 436 0.4× 553 1.1× 47 0.1× 206 0.5× 36 0.1× 199 1.4k

Countries citing papers authored by Lerina Aversano

Since Specialization
Citations

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

Fields of papers citing papers by Lerina Aversano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lerina Aversano

This figure shows the co-authorship network connecting the top 25 collaborators of Lerina Aversano. A scholar is included among the top collaborators of Lerina Aversano 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 Lerina Aversano. Lerina Aversano 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.
Aversano, Lerina, et al.. (2025). What Time Is It? Finding Which Temporal Features is More Useful for Next Activity Prediction. IEEE Open Journal of the Computer Society. 6. 261–271.
2.
Aversano, Lerina, et al.. (2025). Process mining applications in healthcare: a systematic literature review. PeerJ Computer Science. 11. e2613–e2613. 1 indexed citations
3.
Aversano, Lerina, et al.. (2024). Explainable Anomaly Detection of Synthetic Medical IoT Traffic Using Machine Learning. SN Computer Science. 5(5). 5 indexed citations
4.
Aversano, Lerina, et al.. (2024). Characterization of Heart Diseases per Single Lead Using ECG Images and CNN-2D. Sensors. 24(11). 3485–3485. 1 indexed citations
5.
Aversano, Lerina, et al.. (2024). A systematic review on artificial intelligence approaches for smart health devices. PeerJ Computer Science. 10. e2232–e2232. 1 indexed citations
6.
Esposito, Concetta, Mohammed Janneh, Vincenzo Calcagno, et al.. (2024). Artificial Intelligence-assisted Raman Spectroscopy for Liver cancer diagnosis. SHILAP Revista de lepidopterología. 309. 10010–10010. 1 indexed citations
7.
Aversano, Lerina, et al.. (2023). A systematic review on artificial intelligence techniques for detecting thyroid diseases. PeerJ Computer Science. 9. e1394–e1394. 24 indexed citations
8.
Aversano, Lerina, Mario Luca Bernardi, Marta Cimitile, et al.. (2023). Raman Spectroscopy of Cells for Cancer Classification Through Machine Learning. 10. 688–693.
9.
Aversano, Lerina, et al.. (2023). A data-aware explainable deep learning approach for next activity prediction. Engineering Applications of Artificial Intelligence. 126. 106758–106758. 10 indexed citations
10.
Ardimento, Pasquale, Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, & Martina Iammarino. (2022). Using deep temporal convolutional networks to just-in-time forecast technical debt principal. Journal of Systems and Software. 194. 111481–111481. 2 indexed citations
11.
Ardimento, Pasquale, Lerina Aversano, Mario Luca Bernardi, Marta Cimitile, & Martina Iammarino. (2021). Just-in-time software defect prediction using deep temporal convolutional networks. Neural Computing and Applications. 34(5). 3981–4001. 14 indexed citations
12.
Aversano, Lerina, Mario Luca Bernardi, Marta Cimitile, & Riccardo Pecori. (2021). Deep neural networks ensemble to detect COVID-19 from CT scans. Pattern Recognition. 120. 108135–108135. 25 indexed citations
13.
Aversano, Lerina, et al.. (2019). An Empirical Study on the Architecture Instability of Software Projects. International Journal of Software Engineering and Knowledge Engineering. 29(4). 515–545. 4 indexed citations
14.
Aversano, Lerina, et al.. (2013). An approach for restructuring text content. International Conference on Software Engineering. 1225–1228. 2 indexed citations
15.
Aversano, Lerina, et al.. (2007). An empirical study on the evolution of design patterns. 385–394. 64 indexed citations
16.
Aversano, Lerina, Massimiliano Di Penta, & Kunal Taneja. (2006). A genetiv programming approach to support the design of service compositions.. Computer Systems: Science & Engineering. 21. 30 indexed citations
17.
Aversano, Lerina, et al.. (2006). Using Concept Lattices to Support Service Selection. International Journal of Web Services Research. 3(4). 32–51. 16 indexed citations
18.
Aversano, Lerina & Maria Tortorella. (2004). An assessment strategy for identifying legacy system evolution requirements in e Business context: Research Articles. 16(4). 255–276. 1 indexed citations
19.
Aversano, Lerina, et al.. (2004). An algorithm for Web service discovery through their composition. 332–339. 42 indexed citations
20.
Aversano, Lerina, Andrea De Lucia, Matteo Gaeta, & Pierluigi Ritrovato. (2003). GENESIS: A Flexible and Distributed Environment for Cooperative Software Engineering.. Software Engineering and Knowledge Engineering. 497–502. 4 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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