J. Donini

8.1k total citations
10 papers, 22 citations indexed

About

J. Donini is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, J. Donini has authored 10 papers receiving a total of 22 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Nuclear and High Energy Physics, 3 papers in Artificial Intelligence and 2 papers in Electrical and Electronic Engineering. Recurrent topics in J. Donini's work include Particle physics theoretical and experimental studies (6 papers), Particle Detector Development and Performance (6 papers) and Computational Physics and Python Applications (3 papers). J. Donini is often cited by papers focused on Particle physics theoretical and experimental studies (6 papers), Particle Detector Development and Performance (6 papers) and Computational Physics and Python Applications (3 papers). J. Donini collaborates with scholars based in France, Italy and United States. J. Donini's co-authors include Louis Vaslin, Vincent Barra, L. Lista, S. Calvet, M. Volpi, K. Cranmer, M. Bettini, J. Kieseler, Rafael Izbicki and T. Dorigo and has published in prestigious journals such as Nuclear Physics B, 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

J. Donini

6 papers receiving 22 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Donini France	3	18	11	3	3	2	10	22
G. Strong Italy	4	20 1.1×	12 1.1×	4 1.3×	4 1.3×	2 1.0×	6	30
L. K. Graczykowski Poland	5	36 2.0×	7 0.6×	3 1.0×	3 1.0×	2 1.0×	12	45
A. Brinkerhoff United States	2	17 0.9×	7 0.6×	2 0.7×	2 0.7×	1 0.5×	4	20
N. M. Hartmann Germany	3	22 1.2×	7 0.6×	2 0.7×	4 1.3×	4 2.0×	6	29
M. Dunford Germany	3	25 1.4×	9 0.8×	5 1.7×	2 0.7×		7	30
N. Strobbe United States	3	23 1.3×	7 0.6×	2 0.7×	6 2.0×		6	26
F. Beaudette France	3	21 1.2×	5 0.5×	4 1.3×	2 0.7×	1 0.5×	9	22
J. Mechnich Netherlands	3	16 0.9×	5 0.5×	2 0.7×	2 0.7×		4	20
Khristian Kotov United States	1	13 0.7×	5 0.5×	2 0.7×	2 0.7×	1 0.5×	2	15
E. L. Busch United States	1	13 0.7×	5 0.5×	2 0.7×	2 0.7×	1 0.5×	3	15

Countries citing papers authored by J. Donini

Since Specialization

Citations

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

Fields of papers citing papers by J. Donini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Donini

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

All Works

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10 of 10 papers shown

1.

Dorigo, T., Cornelia Arcaro, Muhammad Awais, et al.. (2025). Toward the end-to-end optimization of the SWGO array layout. Nuclear Physics B. 1017. 116934–116934.

2.

Vaslin, Louis, S. Calvet, Vincent Barra, & J. Donini. (2023). pyBumpHunter: A model independent bump hunting tool in Python for high energy physics analyses. arXiv (Cornell University). 4 indexed citations

3.

Calvet, S., et al.. (2023). Codebase release 0.4 for pyBumpHunter. 1 indexed citations

4.

Vaslin, Louis, Vincent Barra, & J. Donini. (2023). GAN-AE: an anomaly detection algorithm for New Physics search in LHC data. The European Physical Journal C. 83(11). 6 indexed citations

5.

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

6.

Donini, J. & L. Lista. (2014). Combination of single top-quark cross-section measurements in the $\mathbf{t}$ channel at $\mathbf{\sqrt{s}=8}$ TeV with the ATLAS and CMS experiments.. CERN Bulletin. 1 indexed citations

7.

Amerio, S., M. Casarsa, G. Cortiana, et al.. (2009). Triggering on B-Jets at CDF II. IEEE Transactions on Nuclear Science. 56(3). 1690–1695.

8.

Amerio, S., M. Casarsa, G. Cortiana, et al.. (2008). Triggering on B-Jets at CDF II. 1156. 2755–2761.

9.

Amerio, S., M. Bettini, P. Catastini, et al.. (2007). The GigaFitter for fast track fitting based on FPGA DSP arrays. CINECA IRIS Institutial research information system (University of Pisa). iii. 2115–2117. 2 indexed citations

10.

Balandras, A., P. Depasse, J. Donini, et al.. (2003). Calibration results of CMS electromagnetic calorimeter photodetectors. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 504(1-3). 335–338.

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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