Silvia Liverani

2.4k total citations
39 papers, 976 citations indexed

About

Silvia Liverani is a scholar working on Artificial Intelligence, Health, Toxicology and Mutagenesis and Statistics and Probability. According to data from OpenAlex, Silvia Liverani has authored 39 papers receiving a total of 976 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 8 papers in Health, Toxicology and Mutagenesis and 8 papers in Statistics and Probability. Recurrent topics in Silvia Liverani's work include Bayesian Methods and Mixture Models (11 papers), Air Quality and Health Impacts (7 papers) and Statistical Methods and Inference (7 papers). Silvia Liverani is often cited by papers focused on Bayesian Methods and Mixture Models (11 papers), Air Quality and Health Impacts (7 papers) and Statistical Methods and Inference (7 papers). Silvia Liverani collaborates with scholars based in United Kingdom, United States and France. Silvia Liverani's co-authors include Sylvia Richardson, Kimberley J. Smith, Mark D. Peterson, Christina Victor, Neil E O’Connell, Nana Anokye, Jennifer Ryan, David I. Hastie, Marta Blangiardo and John Molitor and has published in prestigious journals such as Neurology, Scientific Reports and Hypertension.

In The Last Decade

Silvia Liverani

36 papers receiving 964 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Silvia Liverani United Kingdom 19 234 229 124 123 122 39 976
Rossella Miglio Italy 21 219 0.9× 750 3.3× 251 2.0× 48 0.4× 97 0.8× 54 1.7k
A. John Petkau Canada 18 104 0.4× 242 1.1× 34 0.3× 20 0.2× 79 0.6× 39 1.2k
Xiaoying Zheng China 22 97 0.4× 330 1.4× 38 0.3× 166 1.3× 198 1.6× 52 1.1k
Xin Hao China 20 43 0.2× 99 0.4× 23 0.2× 40 0.3× 114 0.9× 64 962
Thomas Steichen United States 12 36 0.2× 99 0.4× 41 0.3× 50 0.4× 63 0.5× 17 778
Marie‐Abèle Bind United States 24 39 0.2× 1.7k 7.4× 48 0.4× 164 1.3× 295 2.4× 60 2.5k
María Antònia Barceló Spain 21 66 0.3× 385 1.7× 58 0.5× 22 0.2× 43 0.4× 73 1.4k
Yinan Zheng United States 29 41 0.2× 705 3.1× 42 0.3× 393 3.2× 1.1k 8.8× 119 2.6k
Dany Doiron Canada 18 31 0.1× 752 3.3× 32 0.3× 45 0.4× 99 0.8× 51 1.5k
Rudolph P. Rull United States 21 67 0.3× 548 2.4× 164 1.3× 110 0.9× 72 0.6× 68 1.6k

Countries citing papers authored by Silvia Liverani

Since Specialization
Citations

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

Fields of papers citing papers by Silvia Liverani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Silvia Liverani

This figure shows the co-authorship network connecting the top 25 collaborators of Silvia Liverani. A scholar is included among the top collaborators of Silvia Liverani 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 Silvia Liverani. Silvia Liverani 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
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Papathomas, Michail, et al.. (2024). Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels. International Statistical Review. 1 indexed citations
4.
Liverani, Silvia, et al.. (2023). Quantifying the uncertainty of partitions for infinite mixture models. Statistics & Probability Letters. 204. 109930–109930. 1 indexed citations
5.
Coker, Eric S., John Molitor, Silvia Liverani, et al.. (2022). Bayesian profile regression to study the ecologic associations of correlated environmental exposures with excess mortality risk during the first year of the Covid-19 epidemic in lombardy, Italy. Environmental Research. 216(Pt 1). 114484–114484. 3 indexed citations
6.
Ali, Rheeda L., Norman Qureshi, Silvia Liverani, et al.. (2020). Left Atrial Enhancement Correlates With Myocardial Conduction Velocity in Patients With Persistent Atrial Fibrillation. Frontiers in Physiology. 11. 570203–570203. 9 indexed citations
7.
Liverani, Silvia, Lucy Leigh, Irene L. Hudson, & Julie Byles. (2020). Clustering method for censored and collinear survival data. Computational Statistics. 36(1). 35–60. 9 indexed citations
8.
Sterrantino, Anna Freni, Silvia Liverani, Marta Blangiardo, et al.. (2019). Associations between metal constituents of ambient particulate matter and mortality in England: an ecological study. BMJ Open. 9(12). e030140–e030140. 21 indexed citations
9.
Ryan, Jennifer, Mark D. Peterson, Nicola Ryan, et al.. (2019). Mortality due to cardiovascular disease, respiratory disease, and cancer in adults with cerebral palsy. Developmental Medicine & Child Neurology. 61(8). 924–928. 86 indexed citations
10.
Ryan, Jennifer, Mark D. Peterson, Anthony Matthews, et al.. (2019). Noncommunicable disease among adults with cerebral palsy. Neurology. 93(14). e1385–e1396. 36 indexed citations
11.
Coker, Eric S., Silvia Liverani, Jason Su, & John Molitor. (2018). Multi-pollutant Modeling Through Examination of Susceptible Subpopulations Using Profile Regression. Current Environmental Health Reports. 5(1). 59–69. 21 indexed citations
12.
Huang, Ruizhu, et al.. (2018). A Case Study of R Performance Analysis and Optimization. 1. 1–6. 1 indexed citations
13.
Liverani, Silvia, et al.. (2017). Metabolic profiling identifies trehalose as an abundant and diurnally fluctuating metabolite in the microalga Ostreococcus tauri. Metabolomics. 13(6). 68–68. 34 indexed citations
14.
Liverani, Silvia, et al.. (2016). Modelling collinear and spatially correlated data. Spatial and Spatio-temporal Epidemiology. 18. 63–73. 27 indexed citations
15.
Coker, Eric S., Silvia Liverani, Jo Kay Ghosh, et al.. (2016). Multi-pollutant exposure profiles associated with term low birth weight in Los Angeles County. Environment International. 91. 1–13. 62 indexed citations
16.
Mattei, Francesca, Silvia Liverani, Florence Guida, et al.. (2016). Multidimensional analysis of the effect of occupational exposure to organic solvents on lung cancer risk: the ICARE study. Occupational and Environmental Medicine. 73(6). 368–377. 18 indexed citations
17.
Liverani, Silvia, David I. Hastie, Lamiae Azizi, Michail Papathomas, & Sylvia Richardson. (2015). PReMiuM: AnRPackage for Profile Regression Mixture Models Using Dirichlet Processes. Journal of Statistical Software. 64(7). 1–30. 87 indexed citations
18.
Hastie, David I., Silvia Liverani, & Sylvia Richardson. (2014). Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations. Statistics and Computing. 25(5). 1023–1037. 35 indexed citations
19.
Monnier, Annabelle, Silvia Liverani, Régis Bouvet, et al.. (2010). Orchestrated transcription of biological processes in the marine picoeukaryote Ostreococcus exposed to light/dark cycles. BMC Genomics. 11(1). 192–192. 97 indexed citations
20.
Liverani, Silvia, et al.. (2006). Entropy Based Adaptive Particle Filter. Brunel University Research Archive (BURA) (Brunel University London). 4728. 87–90. 1 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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