R. Travaglini

39.6k total citations
27 papers, 50 citations indexed

About

R. Travaglini is a scholar working on Nuclear and High Energy Physics, Radiation and Electrical and Electronic Engineering. According to data from OpenAlex, R. Travaglini has authored 27 papers receiving a total of 50 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Nuclear and High Energy Physics, 15 papers in Radiation and 7 papers in Electrical and Electronic Engineering. Recurrent topics in R. Travaglini's work include Particle Detector Development and Performance (22 papers), Radiation Detection and Scintillator Technologies (15 papers) and Particle physics theoretical and experimental studies (8 papers). R. Travaglini is often cited by papers focused on Particle Detector Development and Performance (22 papers), Radiation Detection and Scintillator Technologies (15 papers) and Particle physics theoretical and experimental studies (8 papers). R. Travaglini collaborates with scholars based in Italy, Germany and United States. R. Travaglini's co-authors include G. Balbi, A. Kugel, D. Falchieri, F. Alfonsi, T. Flick, N. Giangiacomi, A. Gabrielli, Alessandro Montanari, M. Bindi and S. Meneghini and has published in prestigious journals such as Physica D Nonlinear Phenomena, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and IEEE Transactions on Nuclear Science.

In The Last Decade

R. Travaglini

19 papers receiving 50 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
R. Travaglini Italy 5 40 25 18 9 6 27 50
A. Thea United Kingdom 2 49 1.2× 12 0.5× 15 0.8× 11 1.2× 7 1.2× 2 61
T. Shaw United States 5 44 1.1× 17 0.7× 15 0.8× 7 0.8× 4 0.7× 15 46
Marek Gumiński Poland 5 43 1.1× 21 0.8× 9 0.5× 14 1.6× 4 0.7× 15 47
D. Reßing Germany 4 52 1.3× 13 0.5× 12 0.7× 8 0.9× 5 0.8× 14 56
D. M. Newbold United Kingdom 4 56 1.4× 25 1.0× 16 0.9× 16 1.8× 8 1.3× 10 62
G. Balbi Italy 4 37 0.9× 21 0.8× 15 0.8× 17 1.9× 5 0.8× 17 45
P. Mättig Germany 5 28 0.7× 22 0.9× 16 0.9× 9 1.0× 3 0.5× 11 42
M. J. Kortelainen United States 3 24 0.6× 15 0.6× 13 0.7× 12 1.3× 7 1.2× 12 32
G. Marchiori Italy 4 60 1.5× 23 0.9× 29 1.6× 18 2.0× 11 1.8× 6 70
F. Hachon France 3 32 0.8× 11 0.4× 12 0.7× 16 1.8× 12 2.0× 5 40

Countries citing papers authored by R. Travaglini

Since Specialization
Citations

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

Fields of papers citing papers by R. Travaglini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R. Travaglini

This figure shows the co-authorship network connecting the top 25 collaborators of R. Travaglini. A scholar is included among the top collaborators of R. Travaglini 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 R. Travaglini. R. Travaglini 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.
Marca, Rossella Della, et al.. (2025). Spatiotemporal quasiperiodicity induced by all-ages vaccine hesitancy in an SIR model. Physica D Nonlinear Phenomena. 484. 135010–135010.
2.
Bresnahan, Philip J., Sara Rivero‐Calle, John M. Morrison, et al.. (2024). High-resolution ocean color imagery from the SeaHawk-HawkEye CubeSat mission. Scientific Data. 11(1). 1246–1246. 2 indexed citations
3.
4.
Bonacorsi, D., et al.. (2022). Machine Learning inference using PYNQ environment in a AWS EC2 F1 Instance. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 1–1.
5.
Bonacorsi, D., et al.. (2022). Accelerating Machine Learning inference using FPGAs: the PYNQ framework tested on an AWS EC2 F1 Instance. Proceedings of 41st International Conference on High Energy physics — PoS(ICHEP2022). 243–243. 1 indexed citations
6.
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
7.
Travaglini, R., G. Balbi, D. Cavazza, et al.. (2020). A multi-channel trigger and acquisition board for TDC-based readout: application to the cosmic rays detector of the PolarQuEEEst 2018 project.. CERN Document Server (European Organization for Nuclear Research). 150–150.
8.
Travaglini, R., G. Baldazzi, I. DʼAntone, et al.. (2019). A 1 GS/s sampling digitizer designed with interleaved architecture (GSPS) for the LaBr3 detectors of the FAMU experiment. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 22–22. 1 indexed citations
9.
Gabrielli, A., F. Alfonsi, G. D’amen, et al.. (2018). A PCI Express board proposed for the upgrade of the ATLAS TDAQ read-out system. 76–76. 1 indexed citations
10.
Giangiacomi, N., et al.. (2018). New Updates on the ATLAS ROD Board Implementation for Pixel Layers 1 and 2. IEEE Transactions on Nuclear Science. 65(8). 2338–2343.
11.
Travaglini, R., I. DʼAntone, S. Meneghini, L. P. Rignanese, & M Zuffa. (2017). Design and implementation of projects with Xilinx Zynq FPGA: a practical case. Memorie della Societa Astronomica Italiana. 88. 186. 2 indexed citations
12.
Gabrielli, A., M. Backhaus, G. Balbi, et al.. (2015). Firmware development and testing of the ATLAS Pixel Detector / IBL ROD card. Journal of Instrumentation. 10(3). C03037–C03037. 3 indexed citations
13.
Flick, T., Peter Maettig, A. Kugel, et al.. (2015). Firmware development and testing of the ATLAS IBL Back-Of-Crate card. 216–216.
14.
Balbi, G., M. Bindi, D. Falchieri, et al.. (2014). ``The Read-Out Driver'' ROD card for the Insertable B-layer (IBL) detector of the ATLAS experiment: commissioning and upgrade studies for the Pixel Layers 1 and 2. Journal of Instrumentation. 9(1). C01044–C01044. 6 indexed citations
15.
Balbi, G., M. Bindi, D. Falchieri, et al.. (2014). Commissioning of the read-out driver (ROD) card for the ATLAS IBL detector and upgrade studies for the pixel Layers 1 and 2. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 765. 232–234. 1 indexed citations
16.
Polini, A., G. Bruni, M. Bruschi, et al.. (2012). Design of the ATLAS IBL Readout System. Physics Procedia. 37. 1948–1955. 1 indexed citations
17.
Balbi, G., V. D. Cafaro, I. DʼAntone, et al.. (2011). A versatile readout and control system for Silicon photomultipliers. 918–923. 4 indexed citations
18.
Bruni, G., M. Bruschi, I. DʼAntone, et al.. (2011). ATLAS IBL: integration of new HW/SW readout features for the additional layer of Pixel Detector. Journal of Instrumentation. 6(1). C01018–C01018. 1 indexed citations
19.
Falchieri, D., G. Bruni, M. Bruschi, et al.. (2010). Proposal for a readout driver card for the ATLAS Insertable B-Layer. 799–801. 7 indexed citations
20.
Travaglini, R., M Zuffa, G. Torromeo, et al.. (2001). Use of antifuse-FPGAs in the Track-Sorter-Master of the CMS Drift Tube Chambers. CERN Document Server (European Organization for Nuclear Research). 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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