Alessia Suprano

722 citations
21 papers · 444 · h-index 13

Impact in

Papers in

Alessia Suprano

20 papers receiving 428 citations

Peers

Alessia Suprano
Comparison fields: 5 of 42
  • Acoustics and Ultrasonics 29
  • Atomic and Molecular Physics, and Optics 349
  • Artificial Intelligence 255
  • Statistical and Nonlinear Physics 39
  • Biomedical Engineering 122
Replace Emanuele Polino with:
Emanuele Polino Italy
Lu‐Feng Qiao China
Taira Giordani Italy
Gonzalo Carvacho Italy
Shashi Prabhakar India
Lambert Giner Canada
J. A. W. van Houwelingen Switzerland
Ruo-Jing Ren China
Chun-Hua Yuan China
Shengshuai Liu China
Alessia Suprano relative to Emanuele Polino Italy Emanuele Polino's profile →
Citations per field
00.5×1.7×
Emanuele Polino · 1×
Citations per year

Countries citing papers authored by Alessia Suprano

Since Specialization
Citations

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

Fields of papers citing papers by Alessia Suprano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Alessia Suprano, 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 Alessia Suprano Line = papers co-authored together Alessia Suprano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020102
2 201959
3 202059
4 202042
5 202121
6 202118
7 202417
8 202216
9 202115
10 202315
11 202115
12 202213
13 202313
14 202312
15 202212
16 202010
17 20242
18 20251
19 20231
20 20221

About Alessia Suprano

Alessia Suprano is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Biomedical Engineering, Statistical and Nonlinear Physics and Electrical and Electronic Engineering, having authored 21 papers that have together received 444 indexed citations. Recurring topics across this work include Quantum Information and Cryptography (17 papers), Quantum Mechanics and Applications (9 papers), Orbital Angular Momentum in Optics (7 papers), Quantum Computing Algorithms and Architecture (6 papers), Neural Networks and Reservoir Computing (6 papers), Optical Polarization and Ellipsometry (4 papers), Advanced Thermodynamics and Statistical Mechanics (3 papers) and Optical Coherence Tomography Applications (1 paper). The work is most often cited by research in Acoustics and Ultrasonics (29 citations), Atomic and Molecular Physics, and Optics (349 citations), Artificial Intelligence (255 citations), Statistical and Nonlinear Physics (39 citations) and Biomedical Engineering (122 citations). Alessia Suprano has collaborated with scholars based in Italy, Brazil and United Kingdom. Frequent co-authors include Fabio Sciarrino, Emanuele Polino, Nicolò Spagnolo, Taira Giordani, Luca Innocenti, Alessandro Ferraro, Mauro Paternostro, Gonzalo Carvacho, Davide Poderini and Iris Agresti. Their work appears in journals such as PRX Quantum, Physical Review Letters, Advanced Photonics, Nature Communications and Science Advances.

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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