Mária Ercsey-Ravasz

42 papers and 2.2k indexed citations i.

About

Mária Ercsey-Ravasz is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Statistical and Nonlinear Physics. According to data from OpenAlex, Mária Ercsey-Ravasz has authored 42 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 12 papers in Cognitive Neuroscience and 12 papers in Statistical and Nonlinear Physics. Recurrent topics in Mária Ercsey-Ravasz’s work include Neural dynamics and brain function (12 papers), Functional Brain Connectivity Studies (9 papers) and Complex Network Analysis Techniques (8 papers). Mária Ercsey-Ravasz is often cited by papers focused on Neural dynamics and brain function (12 papers), Functional Brain Connectivity Studies (9 papers) and Complex Network Analysis Techniques (8 papers). Mária Ercsey-Ravasz collaborates with scholars based in Romania, United States and Hungary. Mária Ercsey-Ravasz's co-authors include Zoltán Toroczkai, Henry Kennedy, Kenneth Knoblauch, David C. Van Essen, Nikola T. Markov, Camille Lamy, Zoltán Néda, K.-t. Leung, L. A. Jozsa and Zoltán Lakner and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Co-authorship network of co-authors of Mária Ercsey-Ravasz i

Fields of papers citing papers by Mária Ercsey-Ravasz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mária Ercsey-Ravasz. 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 Mária Ercsey-Ravasz. The network helps show where Mária Ercsey-Ravasz may publish in the future.

Countries citing papers authored by Mária Ercsey-Ravasz

Since Specialization
Citations

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