Mario Peruggia

66 total papers · 712 total citations
36 papers, 506 citations indexed

About

Mario Peruggia is a scholar working on Statistics and Probability, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Mario Peruggia has authored 36 papers receiving a total of 506 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Statistics and Probability, 10 papers in Artificial Intelligence and 5 papers in Cognitive Neuroscience. Recurrent topics in Mario Peruggia's work include Statistical Methods and Bayesian Inference (10 papers), Statistical Methods and Inference (8 papers) and Bayesian Methods and Mixture Models (8 papers). Mario Peruggia is often cited by papers focused on Statistical Methods and Bayesian Inference (10 papers), Statistical Methods and Inference (8 papers) and Bayesian Methods and Mixture Models (8 papers). Mario Peruggia collaborates with scholars based in United States, Nepal and Switzerland. Mario Peruggia's co-authors include Jason C. Hsu, Trisha Van Zandt, Steven N. MacEachern, Peter F. Craigmile, Jason C. Hsu, Jeffrey T. Barth, Vito A. Perriello, Thomas J. Santner, Paul M. Suratt and Robert H. Diamond and has published in prestigious journals such as Journal of the American Statistical Association, PEDIATRICS and Endocrinology.

In The Last Decade

Mario Peruggia

34 papers receiving 473 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Mario Peruggia	78	72	54	51	44	36	506
R. Choudary Hanumara	115 1.5×	29 0.4×	96 1.8×	11 0.2×	32 0.7×	32	571
Lei Huang	103 1.3×	73 1.0×	31 0.6×	45 0.9×	5 0.1×	48	482
Xiaochen Xian	45 0.6×	117 1.6×	30 0.6×	87 1.7×	19 0.4×	32	492
Hongshik Ahn	161 2.1×	46 0.6×	62 1.1×	16 0.3×	7 0.2×	51	578
Linda C. Malone	31 0.4×	47 0.7×	94 1.7×	19 0.4×	4 0.1×	28	538
Juan Carlos Correa	107 1.4×	40 0.6×	37 0.7×	10 0.2×	2 0.0×	57	497
Ron Bates	17 0.2×	28 0.4×	165 3.1×	41 0.8×	17 0.4×	38	615
Alexis Boukouvalas	22 0.3×	94 1.3×	37 0.7×	10 0.2×	4 0.1×	23	591
Nikolay Bliznyuk	25 0.3×	47 0.7×	18 0.3×	19 0.4×	4 0.1×	40	550
Andrada E. Ivanescu	101 1.3×	46 0.6×	8 0.1×	32 0.6×	3 0.1×	19	465

Countries citing papers authored by Mario Peruggia

Since Specialization

Citations

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

Fields of papers citing papers by Mario Peruggia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mario Peruggia

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

All Works

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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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