Umberto Picchini

24 papers and 411 indexed citations i.

About

Umberto Picchini is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Umberto Picchini has authored 24 papers receiving a total of 411 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Statistics and Probability, 10 papers in Artificial Intelligence and 4 papers in Molecular Biology. Recurrent topics in Umberto Picchini’s work include Markov Chains and Monte Carlo Methods (11 papers), Gaussian Processes and Bayesian Inference (8 papers) and Statistical Methods and Bayesian Inference (6 papers). Umberto Picchini is often cited by papers focused on Markov Chains and Monte Carlo Methods (11 papers), Gaussian Processes and Bayesian Inference (8 papers) and Statistical Methods and Bayesian Inference (6 papers). Umberto Picchini collaborates with scholars based in Sweden, Denmark and Italy. Umberto Picchini's co-authors include Susanne Ditlevsen, Andrea De Gaetano, Julie Lyng Forman, Andrea Morelli, Monica Rocco, Giorgio Conti, P Pietropaoli, Alessandra Orecchioni, Pasquale Palumbo and J. Van Gelder and has published in prestigious journals such as Critical Care Medicine, Anesthesiology and Statistics in Medicine.

In The Last Decade

Co-authorship network of co-authors of Umberto Picchini i

Fields of papers citing papers by Umberto Picchini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Umberto Picchini

Since Specialization
Citations

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

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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2025