G. Riccio

3.1k total citations
18 papers, 160 citations indexed

About

G. Riccio is a scholar working on Astronomy and Astrophysics, Instrumentation and Artificial Intelligence. According to data from OpenAlex, G. Riccio has authored 18 papers receiving a total of 160 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Astronomy and Astrophysics, 5 papers in Instrumentation and 2 papers in Artificial Intelligence. Recurrent topics in G. Riccio's work include Stellar, planetary, and galactic studies (8 papers), Galaxies: Formation, Evolution, Phenomena (8 papers) and Astronomy and Astrophysical Research (5 papers). G. Riccio is often cited by papers focused on Stellar, planetary, and galactic studies (8 papers), Galaxies: Formation, Evolution, Phenomena (8 papers) and Astronomy and Astrophysical Research (5 papers). G. Riccio collaborates with scholars based in Italy, Germany and United States. G. Riccio's co-authors include M. Brescia, S. Cavuoti, G. Longo, C. Donalek, M. Salvato, S. G. Djorgovski, Valeria Amaro, C. M. Urry, Sabina Tangaro and Andrea Tateo and has published in prestigious journals such as SHILAP Revista de lepidopterología, Monthly Notices of the Royal Astronomical Society and Astronomy and Astrophysics.

In The Last Decade

G. Riccio

15 papers receiving 146 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
G. Riccio Italy	7	106	39	23	20	19	18	160
Vesna Lukic Germany	5	166 1.6×	22 0.6×	20 0.9×	27 1.4×	25 1.3×	6	205
Maayane T. Soumagnac United States	7	189 1.8×	34 0.9×	17 0.7×	8 0.4×	18 0.9×	13	215
D. Tuccillo France	5	226 2.1×	122 3.1×	42 1.8×	22 1.1×	17 0.9×	5	290
T. Kuntzer Switzerland	5	126 1.2×	37 0.9×	8 0.3×	9 0.5×	14 0.7×	8	150
Michelle Ntampaka United States	8	185 1.7×	61 1.6×	26 1.1×	44 2.2×	8 0.4×	15	214
M. V. Costa-Duarte Brazil	7	154 1.5×	56 1.4×	30 1.3×	16 0.8×	3 0.2×	11	173
Ryan Riegel United States	4	214 2.0×	73 1.9×	17 0.7×	34 1.7×	11 0.6×	8	254
M. A. Bershady United States	6	169 1.6×	101 2.6×	15 0.7×	12 0.6×	4 0.2×	9	200
L. Faccioli France	9	175 1.7×	88 2.3×	10 0.4×	35 1.8×	13 0.7×	22	229
Kate Storey-Fisher United States	9	197 1.9×	73 1.9×	9 0.4×	31 1.6×	9 0.5×	13	237

Countries citing papers authored by G. Riccio

Since Specialization

Citations

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

Fields of papers citing papers by G. Riccio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Riccio

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

All Works

Sort: Min cites: Since: Top N: Style:

18 of 18 papers shown

Maruccia, Y., S. Cavuoti, M. Brescia, et al.. (2025). The evolutionary path of star-forming clumps in Hi-GAL. Astronomy and Computing. 53. 100985–100985.

Maruccia, Y., et al.. (2025). An Introduction to Machine Learning Methods for Fraud Detection. Applied Sciences. 15(21). 11787–11787. 1 indexed citations

Maruccia, Y., D. De Cicco, S. Cavuoti, et al.. (2025). Navigating AGN variability with self-organizing maps. Astronomy and Astrophysics. 699. A303–A303.

Paone, Nicola, et al.. (2025). Indirect Measurement of Shooting Distance by Active Thermography. SHILAP Revista de lepidopterología. 5(4). 65–65.

Paone, Nicola, Giuseppe Pandarese, Paolo Castellini, et al.. (2023). Active Thermography for Gunshot Residue (GSR) Pattern Estimation on Textiles. Università Politecnica delle Marche (Università Politecnica delle Marche). 104–109. 3 indexed citations

Zavagno, A., François-Xavier Dupé, E. Schisano, et al.. (2022). Supervised machine learning on Galactic filaments. Astronomy and Astrophysics. 669. A120–A120. 13 indexed citations

Brescia, M., et al.. (2021). Photometric Redshifts With Machine Learning, Lights and Shadows on a Complex Data Science Use Case. Frontiers in Astronomy and Space Sciences. 8. 20 indexed citations

Cavuoti, S., et al.. (2021). Improving the reliability of photometric redshift with machine learning. Monthly Notices of the Royal Astronomical Society. 507(4). 5034–5052. 18 indexed citations

Angora, G., M. Brescia, S. Cavuoti, et al.. (2019). Astroinformatics-based search for globular clusters in the Fornax Deep Survey. Monthly Notices of the Royal Astronomical Society. 490(3). 4080–4106. 4 indexed citations

10.

Brescia, M., M. Salvato, S. Cavuoti, et al.. (2019). Photometric redshifts for X-ray-selected active galactic nuclei in the eROSITA era. Monthly Notices of the Royal Astronomical Society. 489(1). 663–680. 15 indexed citations

11.

Cavuoti, S., et al.. (2019). Star formation rates for photometric samples of galaxies using machine learning methods. Monthly Notices of the Royal Astronomical Society. 486(1). 1377–1391. 17 indexed citations

12.

Brescia, M., S. Cavuoti, Valeria Amaro, et al.. (2018). The astronomical data deluge and the template case of photometric redshifts. arXiv (Cornell University). 3 indexed citations

13.

Vitello, Fabio, ‬‬‬‬‬‬Eva Sciacca, U. Becciani, et al.. (2018). Vialactea Visual Analytics Tool for Star Formation Studies of the Galactic Plane. Publications of the Astronomical Society of the Pacific. 130(990). 84503–84503. 3 indexed citations

14.

Sciacca, ‬‬‬‬‬‬Eva, Fabio Vitello, U. Becciani, et al.. (2017). VIALACTEA science gateway for Milky Way analysis. Future Generation Computer Systems. 94. 947–956. 2 indexed citations

15.

Cavuoti, S., M. Brescia, C. Donalek, et al.. (2016). An analysis of feature relevance in the classification of astronomical transients with machine learning methods. Monthly Notices of the Royal Astronomical Society. 457(3). 3119–3132. 32 indexed citations

16.

Molinari, S., S. Cavuoti, M. Molinaro, et al.. (2016). Integrated data access, visualization and analysis for Galactic Plane surveys: the VIALACTEA case. Proceedings of the International Astronomical Union. 12(S325). 291–298. 1 indexed citations

17.

Tangaro, Sabina, Nicola Amoroso, M. Brescia, et al.. (2015). Feature Selection Based on Machine Learning in MRIs for Hippocampal Segmentation. Computational and Mathematical Methods in Medicine. 2015. 1–10. 24 indexed citations

18.

Sazhin, M. V., et al.. (2010). Gravitational Lens Images Generated by Cosmic Strings. 3(1). 200–206. 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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