Francesco Ceccarelli

783 total citations
43 papers, 444 citations indexed

About

Francesco Ceccarelli is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Biophysics. According to data from OpenAlex, Francesco Ceccarelli has authored 43 papers receiving a total of 444 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Electrical and Electronic Engineering, 22 papers in Artificial Intelligence and 13 papers in Biophysics. Recurrent topics in Francesco Ceccarelli's work include Neural Networks and Reservoir Computing (20 papers), Photonic and Optical Devices (18 papers) and Advanced Fluorescence Microscopy Techniques (13 papers). Francesco Ceccarelli is often cited by papers focused on Neural Networks and Reservoir Computing (20 papers), Photonic and Optical Devices (18 papers) and Advanced Fluorescence Microscopy Techniques (13 papers). Francesco Ceccarelli collaborates with scholars based in Italy, France and Austria. Francesco Ceccarelli's co-authors include Roberto Osellame, Ivan Rech, Angelo Gulinatti, Massimo Ghioni, Simone Piacentini, Andrea Crespi, Giulia Acconcia, Philip Walther, Fabio Sciarrino and Nicolò Spagnolo and has published in prestigious journals such as Nature Photonics, Scientific Reports and Science Advances.

In The Last Decade

Francesco Ceccarelli

38 papers receiving 417 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francesco Ceccarelli Italy 13 214 204 119 114 95 43 444
Arin Can Ülkü Switzerland 13 199 0.9× 39 0.2× 415 3.5× 105 0.9× 330 3.5× 34 743
Rudi Lussana Italy 12 156 0.7× 160 0.8× 517 4.3× 231 2.0× 280 2.9× 27 756
Guido Zambra Italy 13 111 0.5× 307 1.5× 48 0.4× 314 2.8× 32 0.3× 22 539
Jiaju Ma United States 14 354 1.7× 26 0.1× 196 1.6× 55 0.5× 107 1.1× 29 567
Bänz Bessire Switzerland 9 74 0.3× 135 0.7× 82 0.7× 158 1.4× 70 0.7× 17 300
Salma Farahi Switzerland 13 234 1.1× 115 0.6× 81 0.7× 353 3.1× 99 1.0× 22 1.0k
Hyeonseung Yu South Korea 11 72 0.3× 80 0.4× 45 0.4× 334 2.9× 74 0.8× 13 639
Fernando Soldevila Spain 10 64 0.3× 61 0.3× 133 1.1× 265 2.3× 102 1.1× 19 645
Paul‐Antoine Moreau United Kingdom 15 81 0.4× 370 1.8× 130 1.1× 437 3.8× 149 1.6× 28 796
Reuben S. Aspden United Kingdom 11 55 0.3× 272 1.3× 167 1.4× 387 3.4× 159 1.7× 15 815

Countries citing papers authored by Francesco Ceccarelli

Since Specialization
Citations

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

Fields of papers citing papers by Francesco Ceccarelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francesco Ceccarelli

This figure shows the co-authorship network connecting the top 25 collaborators of Francesco Ceccarelli. A scholar is included among the top collaborators of Francesco Ceccarelli 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 Francesco Ceccarelli. Francesco Ceccarelli 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.
Carvacho, Gonzalo, Nicolò Spagnolo, Taira Giordani, et al.. (2025). Photonic quantum convolutional neural networks with adaptive state injection. Advanced Photonics. 7(6).
2.
Ceccarelli, Francesco, et al.. (2025). A 24-mode laser-written universal photonic processor in a glass-based platform. 81–81. 1 indexed citations
3.
Novo, Leonardo, Alessia Suprano, Carlos Tavares, et al.. (2025). Semi-Device-Independent Characterization of Multiphoton Indistinguishability. PRX Quantum. 6(2). 1 indexed citations
4.
Agresti, Iris, Koushik Paul, Simone Piacentini, et al.. (2025). Demonstration of hardware efficient photonic variational quantum algorithm. Physical Review Research. 7(4).
5.
Agresti, Iris, Simone Piacentini, Andrea Crespi, et al.. (2025). Experimental quantum-enhanced kernel-based machine learning on a photonic processor. Nature Photonics. 19(9). 1020–1027. 2 indexed citations
6.
Corrielli, Giacomo, Ivan Labanca, Angelo Gulinatti, et al.. (2025). Laser-written reconfigurable photonic integrated circuit directly coupled to a single-photon avalanche diode array. Light Science & Applications. 14(1). 199–199.
7.
Cimini, Valeria, Mauro Valeri, Simone Piacentini, et al.. (2024). Variational quantum algorithm for experimental photonic multiparameter estimation. npj Quantum Information. 10(1). 16 indexed citations
8.
Giordani, Taira, Gonzalo Carvacho, Nicolò Spagnolo, et al.. (2024). Modular quantum-to-quantum Bernoulli factory in an integrated photonic processor. Nature Photonics. 19(1). 12–19. 2 indexed citations
9.
Piacentini, Simone, et al.. (2024). High‐fidelity and polarization‐insensitive universal photonic processors fabricated by femtosecond laser writing. Nanophotonics. 13(12). 2259–2270. 15 indexed citations
10.
Corrielli, Giacomo, Iris Agresti, Gonzalo Carvacho, et al.. (2024). High-fidelity four-photon GHZ states on chip. npj Quantum Information. 10(1). 15 indexed citations
11.
Cimini, Valeria, Mauro Valeri, Emanuele Polino, et al.. (2023). Deep reinforcement learning for quantum multiparameter estimation. Advanced Photonics. 5(1). 31 indexed citations
12.
Paiè, Petra, Alessia Candeo, Francesco Ceccarelli, et al.. (2023). Structured-light-sheet imaging in an integrated optofluidic platform. Lab on a Chip. 24(1). 34–46. 5 indexed citations
13.
Valeri, Mauro, Valeria Cimini, Simone Piacentini, et al.. (2023). Experimental multiparameter quantum metrology in adaptive regime. Physical Review Research. 5(1). 16 indexed citations
14.
Giordani, Taira, Rafael Wagner, Gonzalo Carvacho, et al.. (2023). Experimental certification of contextuality, coherence, and dimension in a programmable universal photonic processor. Science Advances. 9(44). eadj4249–eadj4249. 14 indexed citations
15.
Spagnolo, Michele, Simone Piacentini, Francesco Massa, et al.. (2022). Experimental photonic quantum memristor. Nature Photonics. 16(4). 318–323. 102 indexed citations
16.
Thomas, S. E., Nicolò Spagnolo, Francesco Ceccarelli, et al.. (2022). Quantifying n-Photon Indistinguishability with a Cyclic Integrated Interferometer. Physical Review X. 12(3). 17 indexed citations
17.
Piacentini, Simone, Taira Giordani, Zhen‐Nan Tian, et al.. (2022). Reconfigurable continuously-coupled 3D photonic circuit for Boson Sampling experiments. npj Quantum Information. 8(1). 30 indexed citations
18.
Thomas, S. E., Nicolò Spagnolo, Francesco Ceccarelli, et al.. (2022). Measuring n-photon Indistinguishability. Conference on Lasers and Electro-Optics. FF2J.6–FF2J.6.
19.
Paiè, Petra, et al.. (2022). Strategies for improved temporal response of glass-based optical switches. Scientific Reports. 12(1). 239–239. 6 indexed citations
20.
Ceccarelli, Francesco, Angelo Gulinatti, Ivan Labanca, Massimo Ghioni, & Ivan Rech. (2018). Red-Enhanced Photon Detection Module Featuring a $32 \times 1$ Single-Photon Avalanche Diode Array. IEEE Photonics Technology Letters. 30(6). 557–560. 9 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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