R. Vio

1.3k total citations
62 papers, 862 citations indexed

About

R. Vio is a scholar working on Astronomy and Astrophysics, Statistical and Nonlinear Physics and Applied Mathematics. According to data from OpenAlex, R. Vio has authored 62 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Astronomy and Astrophysics, 11 papers in Statistical and Nonlinear Physics and 11 papers in Applied Mathematics. Recurrent topics in R. Vio's work include Statistical and numerical algorithms (11 papers), Galaxies: Formation, Evolution, Phenomena (10 papers) and Advanced Statistical Methods and Models (8 papers). R. Vio is often cited by papers focused on Statistical and numerical algorithms (11 papers), Galaxies: Formation, Evolution, Phenomena (10 papers) and Advanced Statistical Methods and Models (8 papers). R. Vio collaborates with scholars based in Italy, Spain and United States. R. Vio's co-authors include Antonello Provenzale, Laura Smith, Giuseppe Murante, W. Wamsteker, P. Andreani, G. Fasano, S. Cristiani, Johnathan M. Bardsley, A. Cellino and V. Zappalà and has published in prestigious journals such as Nature, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

R. Vio

62 papers receiving 803 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
R. Vio Italy 15 350 200 186 80 78 62 862
Vicent J. Martı́nez Spain 24 1.2k 3.3× 336 1.7× 129 0.7× 28 0.3× 104 1.3× 73 1.6k
M. Sadegh Movahed Iran 16 316 0.9× 342 1.7× 589 3.2× 53 0.7× 16 0.2× 63 1.1k
Jeffrey D. Scargle United States 20 742 2.1× 83 0.4× 55 0.3× 23 0.3× 47 0.6× 60 1.3k
A. Noullez France 18 604 1.7× 119 0.6× 88 0.5× 19 0.2× 25 0.3× 39 1.1k
G. Györgyi Hungary 22 61 0.2× 442 2.2× 119 0.6× 113 1.4× 30 0.4× 57 1.2k
Ajit Kembhavi India 19 836 2.4× 57 0.3× 34 0.2× 15 0.2× 197 2.5× 79 1.2k
Paul F. Fougère United States 19 692 2.0× 71 0.4× 41 0.2× 25 0.3× 63 0.8× 41 1.2k
G. Turchetti Italy 19 67 0.2× 666 3.3× 135 0.7× 99 1.2× 29 0.4× 172 1.4k
M. S. Wheatland Australia 29 2.2k 6.4× 151 0.8× 125 0.7× 15 0.2× 39 0.5× 86 2.6k
D. A. Usikov United States 11 151 0.4× 588 2.9× 91 0.5× 210 2.6× 15 0.2× 28 1.1k

Countries citing papers authored by R. Vio

Since Specialization
Citations

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

Fields of papers citing papers by R. Vio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R. Vio

This figure shows the co-authorship network connecting the top 25 collaborators of R. Vio. A scholar is included among the top collaborators of R. Vio 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 R. Vio. R. Vio 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.
Andreani, P., Yusuke Miyamoto, Hiroyuki Kaneko, et al.. (2020). The molecular mass function of the local Universe. Springer Link (Chiba Institute of Technology). 6 indexed citations
2.
Randazzo, Andrea, et al.. (2020). Low-Cost FMCW Radar Human-Vehicle Classification Based on Transfer Learning. CINECA IRIS Institutial Research Information System (University of Genoa). 1–4. 3 indexed citations
3.
Vio, R., Thomas Nagler, & P. Andreani. (2020). Modeling high-dimensional dependence in astronomical data. Astronomy and Astrophysics. 642. A156–A156. 5 indexed citations
4.
Vio, R., P. Andreani, A. D. Biggs, & Natsuki H. Hayatsu. (2019). The correct estimate of the probability of false detection of the matched filter in weak-signal detection problems. Astronomy and Astrophysics. 627. A103–A103. 6 indexed citations
5.
Vio, R. & P. Andreani. (2018). Spectral analysis of unevenly sampled signals: an effective alternative to the Lomb-Scargle periodogram. arXiv (Cornell University). 1 indexed citations
6.
Andreani, P., A. Boselli, L. Ciesla, et al.. (2018). The bivariate luminosity and mass functions of the local HRS galaxy sample. Astronomy and Astrophysics. 617. A33–A33. 14 indexed citations
7.
Vio, R., C. Vergès, & P. Andreani. (2017). The correct estimate of the probability of false detection of the matched filter in weak-signal detection problems. Astronomy and Astrophysics. 604. A115–A115. 8 indexed citations
8.
Vio, R. & P. Andreani. (2016). The correct estimate of the probability of false detection of the matched filter in weak-signal detection problems. Astronomy and Astrophysics. 589. A20–A20. 15 indexed citations
9.
Andreani, P., L. Spinoglio, A. Boselli, et al.. (2014). The bivariateK-band-submillimetre luminosity functions of the local HRS galaxy sample. Astronomy and Astrophysics. 566. A70–A70. 8 indexed citations
10.
Vio, R., P. Andreani, & A. D. Biggs. (2010). Unevenly-sampled signals: a general formalism for the Lomb-Scargle periodogram. Springer Link (Chiba Institute of Technology). 10 indexed citations
11.
Vio, R. & P. Andreani. (2008). A statistical analysis of the “internal linear combination” method in problems of signal separation as in cosmic microwave background observations. Springer Link (Chiba Institute of Technology). 7 indexed citations
12.
Vio, R., Johnathan M. Bardsley, & W. Wamsteker. (2005). Least-squares methods with Poissonian noise: Analysis and comparison with the Richardson-Lucy algorithm. Astronomy and Astrophysics. 436(2). 741–755. 28 indexed citations
13.
Vio, R., Niels Rode Kristensen, Henrik Madsen, & W. Wamsteker. (2005). Time series analysis in astronomy: Limits and potentialities. Astronomy and Astrophysics. 435(2). 773–780. 6 indexed citations
14.
Vio, R., Ping Ma, Weicheng Zhong, et al.. (2004). Estimation of regularization parameters in multiple-image deblurring. Springer Link (Chiba Institute of Technology). 6 indexed citations
15.
Vio, R., James G. Nagy, Luis Tenorio, & W. Wamsteker. (2004). A simple but efficient algorithm for multiple-image deblurring. Astronomy and Astrophysics. 416(1). 403–410. 14 indexed citations
16.
Vio, R., James G. Nagy, Luis Tenorio, et al.. (2003). Digital deblurring of CMB maps: Performance and\nefficient implementation. Springer Link (Chiba Institute of Technology). 5 indexed citations
17.
Vio, R., James G. Nagy, Luis Tenorio, et al.. (2003). Digital deblurring of CMB maps. Astronomy and Astrophysics. 408(3). 835–843. 2 indexed citations
18.
Vio, R., Luis Tenorio, & W. Wamsteker. (2002). On optimal detection of point sources in CMB maps. Astronomy and Astrophysics. 391(2). 789–794. 8 indexed citations
19.
Contarini, Gabriella, et al.. (1996). Spectroscopic observations of the sodium atmosphere of the Moon. Planetary and Space Science. 44(5). 417–420. 10 indexed citations
20.
Fasano, G. & R. Vio. (1988). Fitting a Straight Line with Errors on both Coordinates. 35. 191. 15 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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