Valeria de Paiva

47 papers and 406 indexed citations i.

About

Valeria de Paiva is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Valeria de Paiva has authored 47 papers receiving a total of 406 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Artificial Intelligence, 19 papers in Computational Theory and Mathematics and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Valeria de Paiva’s work include Logic, Reasoning, and Knowledge (24 papers), Logic, programming, and type systems (22 papers) and Natural Language Processing Techniques (16 papers). Valeria de Paiva is often cited by papers focused on Logic, Reasoning, and Knowledge (24 papers), Logic, programming, and type systems (22 papers) and Natural Language Processing Techniques (16 papers). Valeria de Paiva collaborates with scholars based in United States, United Kingdom and Brazil. Valeria de Paiva's co-authors include Gavin Bierman, P. N. Benton, Martin Hyland, Torben Braüner, Alexandre Rademaker, Ann Copestake, Ted Briscoe, Gerard de Melo, Daniel G. Bobrow and R. Stollé and has published in prestigious journals such as Communications of the ACM, Theoretical Computer Science and Computational Linguistics.

In The Last Decade

Co-authorship network of co-authors of Valeria de Paiva i

Fields of papers citing papers by Valeria de Paiva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Valeria de Paiva. 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 Valeria de Paiva. The network helps show where Valeria de Paiva may publish in the future.

Countries citing papers authored by Valeria de Paiva

Since Specialization
Citations

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

Explore authors with similar magnitude of impact

Rankless by CCL
2025