M. Tosi

94.3k total citations
12 papers, 45 citations indexed

About

M. Tosi is a scholar working on Nuclear and High Energy Physics, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, M. Tosi has authored 12 papers receiving a total of 45 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Nuclear and High Energy Physics, 3 papers in Electrical and Electronic Engineering and 2 papers in Computer Networks and Communications. Recurrent topics in M. Tosi's work include Particle physics theoretical and experimental studies (7 papers), Particle Detector Development and Performance (6 papers) and Medical Imaging Techniques and Applications (2 papers). M. Tosi is often cited by papers focused on Particle physics theoretical and experimental studies (7 papers), Particle Detector Development and Performance (6 papers) and Medical Imaging Techniques and Applications (2 papers). M. Tosi collaborates with scholars based in Italy, Switzerland and United States. M. Tosi's co-authors include Florian Goertz, T. Dorigo, A. Carvalho Antunes De Oliveira, C. A. Gottardo, E. Del Re, Simone Morosi, Romano Fantacci, V. Ippolito, Atılım Güneş Baydin and A. Giammanco and has published in prestigious journals such as Journal of High Energy Physics, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and Journal of Physics Conference Series.

In The Last Decade

M. Tosi

8 papers receiving 42 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. Tosi Italy	4	36	5	4	3	3	12	45
L. K. Graczykowski Poland	5	36 1.0×	7 1.4×	3 0.8×	3 1.0×	2 0.7×	12	45
B. Scurlock United States	3	24 0.7×	6 1.2×	5 1.3×	2 0.7×		5	27
T. Antičić Croatia	3	39 1.1×	2 0.4×	3 0.8×	4 1.3×	2 0.7×	10	43
M. Dunford Germany	3	25 0.7×	9 1.8×	5 1.3×	2 0.7×	1 0.3×	7	30
L. Skinnari United States	3	20 0.6×	3 0.6×	5 1.3×	6 2.0×		7	25
J. Couchman United Kingdom	2	34 0.9×	4 0.8×	4 1.0×	2 0.7×		3	37
N. Nikiforou United States	4	34 0.9×	3 0.6×	5 1.3×	8 2.7×		5	35
N. Strobbe United States	3	23 0.6×	7 1.4×	2 0.5×	6 2.0×		6	26
S. Donati Italy	3	26 0.7×	7 1.4×	8 2.0×	9 3.0×	3 1.0×	24	37
B. Stelzer Canada	3	22 0.6×	3 0.6×	3 0.8×	7 2.3×		6	22

Countries citing papers authored by M. Tosi

Since Specialization

Citations

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

Fields of papers citing papers by M. Tosi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Tosi

This figure shows the co-authorship network connecting the top 25 collaborators of M. Tosi. A scholar is included among the top collaborators of M. Tosi 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 M. Tosi. M. Tosi 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:

12 of 12 papers shown

1.

Dorigo, T., et al.. (2025). Unsupervised Particle Tracking with Neuromorphic Computing. Particles. 8(2). 40–40.

2.

Baydin, Atılım Güneş, K. Cranmer, Pablo De Castro Manzano, et al.. (2021). Toward Machine Learning Optimization of Experimental Design. Nuclear Physics News. 31(1). 25–28. 8 indexed citations

3.

Tosi, M.. (2017). The CMS trigger in Run 2. CERN Document Server (European Organization for Nuclear Research). 523–523.

4.

Tosi, M.. (2016). Tracking at High Level Trigger in CMS. Nuclear and Particle Physics Proceedings. 273-275. 2494–2496. 3 indexed citations

5.

Tosi, M. & V. Ippolito. (2016). Search for Dark Matter (experiment). CERN Bulletin. 4–4. 1 indexed citations

6.

Oliveira, A. Carvalho Antunes De, et al.. (2016). Higgs pair production: choosing benchmarks with cluster analysis. Journal of High Energy Physics. 2016(4). 1–28. 23 indexed citations

7.

Tosi, M.. (2015). Tracking at High Level Trigger in CMS. 204–204. 1 indexed citations

8.

Tosi, M.. (2015). Performance of Tracking, b-tagging and Jet/MET reconstruction at the CMS High Level Trigger. Journal of Physics Conference Series. 664(8). 82055–82055. 2 indexed citations

9.

Tosi, M.. (2013). Results on the Search for MSSM Neutral and Charged Higgs bosons (CMS). Journal of Physics Conference Series. 447. 12048–12048.

10.

Donini, J., T. Dorigo, C. Neu, et al.. (2008). Energy calibration of b-quark jets with Z→bb¯ decays at the Tevatron collider. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 596(3). 354–367. 4 indexed citations

11.

Morosi, Simone, et al.. (2004). Implementation of a wideband directional channel model for a units link level simulator. Florence Research (University of Florence). 1. 3381–3385. 2 indexed citations

12.

Re, E. Del, et al.. (2002). IMPLEMENTATION OF WIDEBAND DIRECTIONAL CHANNEL FOR UMTS LINK LEVEL SIMULATOR. CINECA IRIS Institutial research information system (University of Pisa). 0–0. 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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