Massimo Poesio

137 papers and 3.1k indexed citations i.

About

Massimo Poesio is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Massimo Poesio has authored 137 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 110 papers in Artificial Intelligence, 20 papers in Cognitive Neuroscience and 17 papers in Experimental and Cognitive Psychology. Recurrent topics in Massimo Poesio’s work include Natural Language Processing Techniques (72 papers), Topic Modeling (69 papers) and Speech and dialogue systems (47 papers). Massimo Poesio is often cited by papers focused on Natural Language Processing Techniques (72 papers), Topic Modeling (69 papers) and Speech and dialogue systems (47 papers). Massimo Poesio collaborates with scholars based in United Kingdom, Italy and Germany. Massimo Poesio's co-authors include Ron Artstein, Renata Vieira, Tommaso Fornaciari, Udo Kruschwitz, Brian Murphy, Silviu Paun, Yannick Versley, Jon Chamberlain, Mijail A. Kabadjov and Andrew Anderson and has published in prestigious journals such as Bioinformatics, NeuroImage and Journal of Cognitive Neuroscience.

In The Last Decade

Co-authorship network of co-authors of Massimo Poesio i

Fields of papers citing papers by Massimo Poesio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Massimo Poesio

Since Specialization
Citations

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