A. Giannini

8.3k citations
3 papers · 5 · h-index 2

Impact in

Papers in

    • Particle physics theoretical and experimental studies 3
    • High-Energy Particle Collisions Research 3
    • Particle Detector Development and Performance 2
    • Quantum Chromodynamics and Particle Interactions 1
Journals
Applied Sciences (2 papers)CERN Document Server (European Organization for Nuclear Research) (1 paper)
Partner nations
ItalyChina

In The Last Decade

A. Giannini

3 papers receiving 4 citations

Peers

A. Giannini
Comparison fields: 5 of 6
  • Energy Engineering and Power Technology 1
  • Nuclear and High Energy Physics 3
  • Computer Networks and Communications 2
  • Artificial Intelligence 2
  • Computer Vision and Pattern Recognition 1
Replace M. Zdybał with:
M. Zdybał Poland
B. Schlag Switzerland
S. Bjelogrlic Portugal
C. Hills United Kingdom
F. Cirotto Italy
S. Auricchio Italy
W. Redjeb Switzerland
A. Cagnotta Italy
Yannik Rath Germany
Bruno Afonso Fontana Santos Alves Switzerland
A. Giannini relative to M. Zdybał Poland M. Zdybał's profile →
Citations per field
00.5×
M. Zdybał · 1×
Citations per year

Countries citing papers authored by A. Giannini

Since Specialization
Citations

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

Fields of papers citing papers by A. Giannini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 2 scholars most cited alongside A. Giannini, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with A. Giannini Line = papers co-authored together A. Giannini links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown
#Work
1 20233
2 20221
3
Machine Learning methods for diboson searches in semi-leptonic final states with the ATLAS experiment at LHC
20201

About A. Giannini

A. Giannini is a scholar working on Nuclear and High Energy Physics, Infectious Diseases, Organic Chemistry, Surgery and Communication, having authored 3 papers that have together received 5 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (3 papers), High-Energy Particle Collisions Research (3 papers), Particle Detector Development and Performance (2 papers) and Quantum Chromodynamics and Particle Interactions (1 paper). The work is most often cited by research in Energy Engineering and Power Technology (1 citation), Nuclear and High Energy Physics (3 citations), Computer Networks and Communications (2 citations), Artificial Intelligence (2 citations) and Computer Vision and Pattern Recognition (1 citation). A. Giannini has collaborated with scholars based in Italy and China. Frequent co-authors include S. Auricchio and F. Cirotto. Their work appears in journals such as Applied Sciences and CERN Document Server (European Organization for Nuclear Research).

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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