L. Giommi

6.4k total citations
17 papers, 70 citations indexed

About

L. Giommi is a scholar working on Computer Networks and Communications, Nuclear and High Energy Physics and Artificial Intelligence. According to data from OpenAlex, L. Giommi has authored 17 papers receiving a total of 70 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Networks and Communications, 8 papers in Nuclear and High Energy Physics and 4 papers in Artificial Intelligence. Recurrent topics in L. Giommi's work include Particle physics theoretical and experimental studies (8 papers), Distributed and Parallel Computing Systems (8 papers) and Advanced Data Storage Technologies (6 papers). L. Giommi is often cited by papers focused on Particle physics theoretical and experimental studies (8 papers), Distributed and Parallel Computing Systems (8 papers) and Advanced Data Storage Technologies (6 papers). L. Giommi collaborates with scholars based in Italy, United States and Switzerland. L. Giommi's co-authors include D. Bonacorsi, В. Е. Кузнецов, T. Wildish, Valentin Kuznetsov, D. Spiga, L. Rinaldi, Fabio Viola, T. Diotalevi, Elisabetta Ronchieri and Lucia Morganti and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Cloud Computing and Journal of Physics Conference Series.

In The Last Decade

L. Giommi

16 papers receiving 66 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
L. Giommi Italy 4 42 28 15 12 11 17 70
T. Frazier United States 4 57 1.4× 31 1.1× 30 2.0× 9 0.8× 6 0.5× 5 77
S. Vejcik United States 4 26 0.6× 19 0.7× 26 1.7× 3 0.3× 6 0.5× 10 57
Mansoor Farooq India 6 42 1.0× 14 0.5× 17 1.1× 3 0.3× 8 0.7× 26 70
Benoît Fraikin Canada 4 24 0.6× 28 1.0× 15 1.0× 7 0.6× 10 58
D. Jovanovic Netherlands 5 6 0.1× 17 0.6× 9 0.6× 13 1.1× 10 0.9× 25 73
Konstantin Shagin Israel 6 69 1.6× 20 0.7× 27 1.8× 10 0.8× 14 87
Junmin Gu United States 7 108 2.6× 10 0.4× 18 1.2× 3 0.3× 4 0.4× 22 122
Olivier Fourmaux France 5 72 1.7× 19 0.7× 9 0.6× 4 0.3× 17 90
Philippe Dhaussy France 5 12 0.3× 19 0.7× 11 0.7× 6 0.5× 16 62
Karl M. Göschka Austria 5 22 0.5× 26 0.9× 17 1.1× 6 0.5× 23 57

Countries citing papers authored by L. Giommi

Since Specialization
Citations

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

Fields of papers citing papers by L. Giommi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of L. Giommi

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

All Works

17 of 17 papers shown
1.
Giommi, L., et al.. (2025). Developments on the “Machine Learning as a Service for High Energy Physics” Framework and Related Cloud Native Solution. IEEE Transactions on Cloud Computing. 13(1). 429–440. 1 indexed citations
2.
3.
Giommi, L., D. Spiga, В. Е. Кузнецов, & D. Bonacorsi. (2024). Progress on cloud native solution of Machine Learning as a Service for HEP. SHILAP Revista de lepidopterología. 295. 7040–7040. 1 indexed citations
4.
Ronchieri, Elisabetta, et al.. (2024). Anomaly Detection in Data Center IT & Physical Infrastructure. SHILAP Revista de lepidopterología. 295. 7004–7004. 1 indexed citations
5.
Anderlini, L., T. Boccali, Stefano Dal Pra, et al.. (2024). ML_INFN project: Status report and future perspectives. SHILAP Revista de lepidopterología. 295. 8013–8013. 1 indexed citations
6.
7.
Giommi, L., D. Spiga, В. Е. Кузнецов, & D. Bonacorsi. (2022). Prototype of a cloud native solution of Machine Learning as Service for HEP. Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022). 968–968. 1 indexed citations
8.
Giommi, L., et al.. (2022). Cloud native approach for Machine Learning as a Service for High Energy Physics. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 12–12. 2 indexed citations
9.
Giommi, L., Valentin Kuznetsov, D. Bonacorsi, & D. Spiga. (2021). Machine Learning as a Service for High Energy Physics on heterogeneous computing resources. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 19–19. 3 indexed citations
10.
Vale, T. Dias Do, F. Legger, J. Schovancova, et al.. (2020). Operational Intelligence for Distributed Computing Systems for Exascale Science. SHILAP Revista de lepidopterología. 245. 3017–3017. 3 indexed citations
11.
Giommi, L., et al.. (2019). Big Data Analysis for Predictive Maintenance at the INFN-CNAF Data Center using Machine Learning Approaches. SHILAP Revista de lepidopterología. 448–451. 5 indexed citations
12.
Giommi, L., D. Bonacorsi, T. Diotalevi, et al.. (2019). Towards Predictive Maintenance with Machine Learning at the INFN-CNAF computing centre. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 3–3. 8 indexed citations
13.
Bonacorsi, D., Valentin Kuznetsov, L. Giommi, et al.. (2018). Progress on Machine and Deep Learning applications in CMS Computing. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 22–22. 1 indexed citations
14.
Giommi, L., D. Bonacorsi, & Valentin Kuznetsov. (2018). Prototype of Machine Learning “as a Service” for CMS Physics in Signal vs Background discrimination. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 93–93. 2 indexed citations
15.
Кузнецов, В. Е., et al.. (2016). Predicting dataset popularity for the CMS experiment. Journal of Physics Conference Series. 762. 12048–12048. 11 indexed citations
16.
Bonacorsi, D., T. Wildish, L. Giommi, & В. Е. Кузнецов. (2016). Exploring Patterns and Correlations in CMS Computing Operations Data with Big Data Analytics Techniques. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 8–8. 2 indexed citations
17.
Giommi, L., et al.. (1998). Real-time anomaly detection in data centers for log-based predictive maintenance using an evolving fuzzy-rule-based approach. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 27 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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