Matej Vecerík

3 papers and 557 indexed citations i.

About

Matej Vecerík is a scholar working on Artificial Intelligence, Economics and Econometrics and Management Science and Operations Research. According to data from OpenAlex, Matej Vecerík has authored 3 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Economics and Econometrics and 1 paper in Management Science and Operations Research. Recurrent topics in Matej Vecerík’s work include Reinforcement Learning in Robotics (3 papers), Sports Analytics and Performance (2 papers) and Evolutionary Algorithms and Applications (2 papers). Matej Vecerík is often cited by papers focused on Reinforcement Learning in Robotics (3 papers), Sports Analytics and Performance (2 papers) and Evolutionary Algorithms and Applications (2 papers). Matej Vecerík collaborates with scholars based in United Kingdom and United States. Matej Vecerík's co-authors include Tom Schaul, Ian Osband, John Agapiou, Audrūnas Gruslys, Marc Lanctot, Gabriel Dulac-Arnold, Todd Hester, Joel Z. Leibo, Olivier Pietquin and John Quan and has published in prestigious journals such as arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence and National Conference on Artificial Intelligence.

In The Last Decade

Co-authorship network of co-authors of Matej Vecerík i

Fields of papers citing papers by Matej Vecerík

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Matej Vecerík

Since Specialization
Citations

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