Alessandra Guglielmi

1.1k total citations
70 papers, 610 citations indexed

About

Alessandra Guglielmi is a scholar working on Artificial Intelligence, Statistics and Probability and Oncology. According to data from OpenAlex, Alessandra Guglielmi has authored 70 papers receiving a total of 610 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 24 papers in Statistics and Probability and 17 papers in Oncology. Recurrent topics in Alessandra Guglielmi's work include Bayesian Methods and Mixture Models (34 papers), Statistical Methods and Inference (15 papers) and Statistical Methods and Bayesian Inference (12 papers). Alessandra Guglielmi is often cited by papers focused on Bayesian Methods and Mixture Models (34 papers), Statistical Methods and Inference (15 papers) and Statistical Methods and Bayesian Inference (12 papers). Alessandra Guglielmi collaborates with scholars based in Italy, United States and United Kingdom. Alessandra Guglielmi's co-authors include James O. Berger, Raffaele Argiento, Alberto Sobrero, Giulia Di Nunno, Eugenio Regazzini, C. Aschele, Fabio Puglisi, Francesco Grossi, Antonio Pievatolo and Richard L. Tweedie and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

Alessandra Guglielmi

61 papers receiving 581 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alessandra Guglielmi Italy 14 283 231 164 95 73 70 610
Andrej Yu. Yakovlev United States 20 320 1.1× 737 3.2× 222 1.4× 281 3.0× 103 1.4× 69 1.5k
Leonid Hanin United States 20 43 0.2× 105 0.5× 265 1.6× 134 1.4× 175 2.4× 69 884
Anup Dewanji India 15 64 0.2× 294 1.3× 74 0.5× 87 0.9× 38 0.5× 63 817
Y. P. Mack United States 14 274 1.0× 688 3.0× 58 0.4× 21 0.2× 30 0.4× 22 1.1k
Marcel Dettling Switzerland 11 349 1.2× 162 0.7× 58 0.4× 772 8.1× 147 2.0× 19 1.2k
Murray D. Burke Canada 10 71 0.3× 256 1.1× 141 0.9× 77 0.8× 30 0.4× 23 549
Robert Bartôszyński United States 10 73 0.3× 138 0.6× 56 0.3× 32 0.3× 13 0.2× 36 390
Zhenming Shun United States 9 76 0.3× 258 1.1× 87 0.5× 175 1.8× 58 0.8× 21 671
Norberto Corral Spain 17 219 0.8× 344 1.5× 84 0.5× 26 0.3× 91 1.2× 46 658
Weichen Wang United States 9 49 0.2× 162 0.7× 16 0.1× 153 1.6× 56 0.8× 22 466

Countries citing papers authored by Alessandra Guglielmi

Since Specialization
Citations

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

Fields of papers citing papers by Alessandra Guglielmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alessandra Guglielmi

This figure shows the co-authorship network connecting the top 25 collaborators of Alessandra Guglielmi. A scholar is included among the top collaborators of Alessandra Guglielmi 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 Alessandra Guglielmi. Alessandra Guglielmi 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.
Guglielmi, Alessandra, et al.. (2025). BayesMix: Bayesian Mixture Models in C++. Journal of Statistical Software. 112(9).
2.
Ardagna, Danilo, et al.. (2025). Discrete Bayesian Optimization via Machine Learning. Performance Evaluation. 169. 102487–102487.
3.
Bernardi, Stella, Stefania Zovato, Gianmaria Pennelli, et al.. (2025). A novel germline (c.314T>A) SDHB variant in metastatic paraganglioma: case report and literature review. Frontiers in Endocrinology. 16. 1577421–1577421.
4.
Ardagna, Danilo, et al.. (2024). Integrating Bayesian Optimization and Machine Learning for the Optimal Configuration of Cloud Systems. IEEE Transactions on Cloud Computing. 12(1). 277–294. 4 indexed citations
5.
Guglielmi, Alessandra, et al.. (2022). Bayesian modeling and clustering for spatio-temporal areal data: An application to Italian unemployment. arXiv (Cornell University). 4 indexed citations
6.
Pegoraro, M., et al.. (2021). Spatially dependent mixture models via the logistic multivariate CAR prior. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 3 indexed citations
7.
Argiento, Raffaele, et al.. (2021). MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes. Journal of Computational and Graphical Statistics. 31(2). 422–435. 12 indexed citations
8.
9.
Giudici, Fabiola, et al.. (2021). EGFR mutation analysis on circulating free DNA in NSCLC: a single-center experience. Journal of Cancer Research and Clinical Oncology. 147(8). 2301–2307. 1 indexed citations
10.
Iorio, Maria De, et al.. (2019). Bayesian Autoregressive Frailty Models for Inference in Recurrent Events. The International Journal of Biostatistics. 16(1). 2 indexed citations
11.
Guglielmi, Alessandra, et al.. (2016). A semiparametric Bayesian joint model for multiple mixed-type outcomes: an application to acute myocardial infarction. Advances in Data Analysis and Classification. 12(2). 399–423. 2 indexed citations
12.
Argiento, Raffaele, Alessandra Guglielmi, & Antonio Pievatolo. (2013). Estimation, prediction and interpretation of NGG random effects models: an application to Kevlar fibre failure times. Statistical Papers. 55(3). 805–826. 2 indexed citations
13.
Guglielmi, Alessandra, et al.. (2013). A Simple Class of Bayesian Nonparametric Autoregression Models. Bayesian Analysis. 8(1). 63–88. 25 indexed citations
14.
Guglielmi, Alessandra, et al.. (2013). Semiparametric Bayesian Models for Clustering and Classification in the Presence of Unbalanced In-Hospital Survival. Journal of the Royal Statistical Society Series C (Applied Statistics). 63(1). 25–46. 14 indexed citations
15.
Epifani, Ilenia, et al.. (2009). Moment-Based Approximations for the Law of Functionals of Dirichlet Processes. Molecular Oncology. 16(5). 1119–1131. 1 indexed citations
16.
Pessino, A., Salvatore Artale, Stefania Sciallero, et al.. (2007). First-line single-agent cetuximab in patients with advanced colorectal cancer. Annals of Oncology. 19(4). 711–716. 38 indexed citations
17.
Guglielmi, Alessandra & Alberto Sobrero. (2007). Second-line therapy for advanced colorectal cancer.. PubMed. 1(2). 57–63. 21 indexed citations
18.
Epifani, Ilenia, et al.. (2005). A stochastic equation for the law of the random Dirichlet variance. Statistics & Probability Letters. 76(5). 495–502. 7 indexed citations
19.
Guglielmi, Alessandra. (1998). Risultati sulle distribuzioni di medie di un processo di Dirichlet. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 125–128. 1 indexed citations
20.
Guglielmi, Alessandra, et al.. (1998). Non-informative invariant priors yield peculiar marginals. Communication in Statistics- Theory and Methods. 27(9). 2293–2306. 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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