Andrea Ceschini

503 total citations · 1 hit paper
19 papers, 224 citations indexed

About

Andrea Ceschini is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Andrea Ceschini has authored 19 papers receiving a total of 224 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 5 papers in Computational Theory and Mathematics and 3 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Andrea Ceschini's work include Quantum Computing Algorithms and Architecture (13 papers), Quantum Information and Cryptography (8 papers) and Quantum-Dot Cellular Automata (4 papers). Andrea Ceschini is often cited by papers focused on Quantum Computing Algorithms and Architecture (13 papers), Quantum Information and Cryptography (8 papers) and Quantum-Dot Cellular Automata (4 papers). Andrea Ceschini collaborates with scholars based in Italy, United States and Greece. Andrea Ceschini's co-authors include Massimo Panella, Rui-Hao Li, Kostas Blekos, Antonello Rosato, Dario Gerace, Bertrand Le Saux, Rodolfo Araneo, Andrea Carbone, David Windridge and Michele Grossi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Physics Reports.

In The Last Decade

Andrea Ceschini

17 papers receiving 212 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review on Quantum Approximate Optimization Algorithm and its variants

2024 130 citations Kostas Blekos, Andrea Ceschini et al. Physics Reports profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Andrea Ceschini Italy	7	160	40	38	36	15	19	224
Andrea Skolik Netherlands	6	375 2.3×	80 2.0×	55 1.4×	101 2.8×	10 0.7×	8	412
Florian Neukart Netherlands	6	164 1.0×	49 1.2×	16 0.4×	32 0.9×	22 1.5×	30	237
Lucian Prodan Romania	10	111 0.7×	40 1.0×	89 2.3×	34 0.9×	17 1.1×	53	229
Donny Greenberg United States	3	116 0.7×	22 0.6×	17 0.4×	22 0.6×	12 0.8×	3	167
Christian Deppe Germany	8	92 0.6×	34 0.8×	96 2.5×	24 0.7×	34 2.3×	22	198
Janis Nötzel Germany	10	163 1.0×	22 0.6×	115 3.0×	68 1.9×	50 3.3×	51	249
Oliver Maurhart Austria	6	200 1.3×	16 0.4×	24 0.6×	142 3.9×	25 1.7×	11	246
Igor Potapov United Kingdom	8	79 0.5×	127 3.2×	20 0.5×	8 0.2×	31 2.1×	53	211
Shengyu Zhang China	7	65 0.4×	17 0.4×	50 1.3×	14 0.4×	64 4.3×	26	179
Satoshi Matsubara Japan	8	78 0.5×	38 0.9×	193 5.1×	6 0.2×	29 1.9×	11	276

Countries citing papers authored by Andrea Ceschini

Since Specialization

Citations

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

Fields of papers citing papers by Andrea Ceschini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrea Ceschini

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

All Works

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19 of 19 papers shown

Ceschini, Andrea, et al.. (2025). A hybrid quantum-neural network for heart disease classification. Biomedical Signal Processing and Control. 113. 109185–109185.

Ceschini, Andrea, et al.. (2025). On hybrid quanvolutional neural networks optimization. Quantum Machine Intelligence. 7(1). 3 indexed citations

Ceschini, Andrea, et al.. (2025). A study on quantum graph neural networks applied to molecular physics. Physica Scripta. 100(6). 65126–65126. 1 indexed citations

Blekos, Kostas, et al.. (2024). A review on Quantum Approximate Optimization Algorithm and its variants. Physics Reports. 1068. 1–66. 130 indexed citations breakdown →

Sebastianelli, Alessandro, Federico Serva, Andrea Ceschini, et al.. (2024). Machine learning forecast of surface solar irradiance from meteo satellite data. Remote Sensing of Environment. 315. 114431–114431. 3 indexed citations

Ceschini, Andrea, Antonello Rosato, & Massimo Panella. (2024). A variational approach to quantum gated recurrent units. Journal of Physics Communications. 8(8). 85004–85004. 2 indexed citations

Ceschini, Andrea, et al.. (2024). A Layerwise-Multi-Angle Approach to Fine-Tuning the Quantum Approximate Optimization Algorithm. IRIS Research product catalog (Sapienza University of Rome). 1–8.

Ceschini, Andrea, et al.. (2024). Q-SCALE: Quantum Computing-Based Sensor Calibration for Advanced Learning and Efficiency. IRIS Research product catalog (Sapienza University of Rome). 306–314. 1 indexed citations

Ceschini, Andrea, et al.. (2024). Quantum latent diffusion models. Quantum Machine Intelligence. 6(2). 3 indexed citations

10.

Ceschini, Andrea, et al.. (2023). A General Approach to Dropout in Quantum Neural Networks. Advanced Quantum Technologies. 8(12). 10 indexed citations

11.

Ceschini, Andrea, Antonello Rosato, & Massimo Panella. (2023). Modular quantum circuits for secure communication. SHILAP Revista de lepidopterología. 4(4). 208–217. 3 indexed citations

12.

Blekos, Kostas, et al.. (2023). A Review on Quantum Approximate Optimization Algorithm and its Variants. arXiv (Cornell University). 3 indexed citations

13.

Grossi, Michele, Andrea Ceschini, Antonio Mandarino, et al.. (2023). Resource saving via ensemble techniques for quantum neural networks. Quantum Machine Intelligence. 5(2). 7 indexed citations

14.

Ceschini, Andrea, et al.. (2022). Multivariate Time Series Analysis for Electrical Power Theft Detection in the Distribution Grid. 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 1–5. 2 indexed citations

15.

Ceschini, Andrea, Antonello Rosato, & Massimo Panella. (2022). Hybrid Quantum-Classical Recurrent Neural Networks for Time Series Prediction. 2022 International Joint Conference on Neural Networks (IJCNN). 1–8. 18 indexed citations

16.

Rosato, Antonello, et al.. (2022). A FAST DEEP LEARNING TECHNIQUE FOR WI-FI-BASED HUMAN ACTIVITY RECOGNITION. Electromagnetic waves. 174. 127–141. 15 indexed citations

17.

Ceschini, Andrea, et al.. (2021). Deep Neural Networks for Electric Energy Theft and Anomaly Detection in the Distribution Grid. IRIS Research product catalog (Sapienza University of Rome). 1–5. 6 indexed citations

18.

Ceschini, Andrea, Antonello Rosato, & Massimo Panella. (2021). Design of an LSTM Cell on a Quantum Hardware. IEEE Transactions on Circuits & Systems II Express Briefs. 69(3). 1822–1826. 13 indexed citations

19.

Ceschini, Andrea, et al.. (2021). Multivariate Prediction of Energy Time Series by Autoencoded LSTM Networks. IRIS Research product catalog (Sapienza University of Rome). 4 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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