T. Diotalevi

6.7k total citations
6 papers, 19 citations indexed

About

T. Diotalevi is a scholar working on Computer Networks and Communications, Nuclear and High Energy Physics and Artificial Intelligence. According to data from OpenAlex, T. Diotalevi has authored 6 papers receiving a total of 19 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Networks and Communications, 4 papers in Nuclear and High Energy Physics and 2 papers in Artificial Intelligence. Recurrent topics in T. Diotalevi's work include Particle physics theoretical and experimental studies (4 papers), Distributed and Parallel Computing Systems (3 papers) and Particle Detector Development and Performance (3 papers). T. Diotalevi is often cited by papers focused on Particle physics theoretical and experimental studies (4 papers), Distributed and Parallel Computing Systems (3 papers) and Particle Detector Development and Performance (3 papers). T. Diotalevi collaborates with scholars based in Italy, Switzerland and United States. T. Diotalevi's co-authors include D. Bonacorsi, L. Rinaldi, Lucia Morganti, R. Travaglini, C. Battilana, L. Giommi, Elisabetta Ronchieri, N. Magini, Valentin Kuznetsov and T. Wildish and has published in prestigious journals such as SHILAP Revista de lepidopterología, Machine Learning Science and Technology and Journal of Physics Conference Series.

In The Last Decade

T. Diotalevi

6 papers receiving 16 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
T. Diotalevi Italy	3	9	7	5	4	3	6	19
D.V. Amelin Germany	3	6 0.7×	10 1.4×	4 0.8×	3 0.8×		4	22
G. Watts United States	3	14 1.6×	9 1.3×	5 1.0×	1 0.3×	4 1.3×	13	20
F. Carena Switzerland	3	11 1.2×	13 1.9×	3 0.6×	1 0.3×	2 0.7×	8	19
Daniel Funke Germany	3	12 1.3×	9 1.3×	3 0.6×			6	20
T. Le Flour France	4	14 1.6×	6 0.9×	5 1.0×		4 1.3×	7	24
C. Ionita Switzerland	3	18 2.0×	12 1.7×	3 0.6×		4 1.3×	5	23
A. Artamonov Russia	3	3 0.3×	6 0.9×	4 0.8×	2 0.5×		9	20
G. Cerminara United States	3	7 0.8×	15 2.1×	15 3.0×	2 0.5×	1 0.3×	6	27
J. Sloper Switzerland	4	23 2.6×	13 1.9×	4 0.8×	3 0.8×	14 4.7×	9	27
Bertrand Bellenot Switzerland	3	16 1.8×	15 2.1×	3 0.6×		8 2.7×	7	24

Countries citing papers authored by T. Diotalevi

Since Specialization

Citations

This map shows the geographic impact of T. Diotalevi'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 T. Diotalevi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Diotalevi more than expected).

Fields of papers citing papers by T. Diotalevi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Diotalevi

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

All Works

Sort: Min cites: Since: Top N: Style:

6 of 6 papers shown

1.

Diotalevi, T., et al.. (2022). Improving parametric neural networks for high-energy physics (and beyond). Machine Learning Science and Technology. 3(3). 35017–35017. 2 indexed citations

2.

Diotalevi, T., et al.. (2021). Deep Learning fast inference on FPGA for CMS Muon Level-1 Trigger studies. CERN Document Server (European Organization for Nuclear Research). 5–5. 3 indexed citations

3.

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

4.

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

5.

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

6.

Bonacorsi, D., et al.. (2015). Monitoring data transfer latency in CMS computing operations. Journal of Physics Conference Series. 664(3). 32033–32033. 2 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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