Doina Precup

173 papers and 5.6k indexed citations i.

About

Doina Precup is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Doina Precup has authored 173 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 119 papers in Artificial Intelligence, 34 papers in Computational Theory and Mathematics and 31 papers in Management Science and Operations Research. Recurrent topics in Doina Precup’s work include Reinforcement Learning in Robotics (72 papers), Machine Learning and Algorithms (24 papers) and Formal Methods in Verification (21 papers). Doina Precup is often cited by papers focused on Reinforcement Learning in Robotics (72 papers), Machine Learning and Algorithms (24 papers) and Formal Methods in Verification (21 papers). Doina Precup collaborates with scholars based in Canada, United States and United Kingdom. Doina Precup's co-authors include Richard S. Sutton, Satinder Singh, Joëlle Pineau, David Meger, Philip Bachman, Peter Henderson, Riashat Islam, Pierre‐Luc Bacon, Jean Harb and Tal Arbel and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Bioinformatics.

In The Last Decade

Co-authorship network of co-authors of Doina Precup i

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Fields of papers citing papers by Doina Precup

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Doina Precup

Since Specialization

Citations

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