Maria Eskevich

52 total papers · 607 total citations
29 papers, 225 citations indexed

About

Maria Eskevich is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Maria Eskevich has authored 29 papers receiving a total of 225 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 12 papers in Computer Vision and Pattern Recognition and 4 papers in Signal Processing. Recurrent topics in Maria Eskevich's work include Topic Modeling (11 papers), Natural Language Processing Techniques (11 papers) and Video Analysis and Summarization (11 papers). Maria Eskevich is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (11 papers) and Video Analysis and Summarization (11 papers). Maria Eskevich collaborates with scholars based in Ireland, Netherlands and France. Maria Eskevich's co-authors include Gareth J. F. Jones, Roeland Ordelman, Robin Aly, Shu Chen, Benoît Huet, Martha Larson, Sravana Reddy, Rosie Jones, Ben Carterette and Ann Clifton and has published in prestigious journals such as Language Resources and Evaluation, Computer Speech & Language and IEEE Multimedia.

In The Last Decade

Maria Eskevich

26 papers receiving 191 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Maria Eskevich 127 125 50 21 12 29 225
Sairam Gurajada 146 1.1× 86 0.7× 38 0.8× 36 1.7× 5 0.4× 20 195
Prachi Jain 154 1.2× 34 0.3× 59 1.2× 16 0.8× 4 0.3× 28 215
Sajjadur Rahman 92 0.7× 141 1.1× 105 2.1× 36 1.7× 2 0.2× 22 235
Eric Malmi 225 1.8× 37 0.3× 16 0.3× 40 1.9× 6 0.5× 25 302
Md Abul Bashar 109 0.9× 56 0.4× 11 0.2× 28 1.3× 5 0.4× 23 198
He Zhao 154 1.2× 60 0.5× 12 0.2× 29 1.4× 6 0.5× 23 237
Koen Deschacht 239 1.9× 96 0.8× 18 0.4× 62 3.0× 3 0.3× 13 316
Seung-won Hwang 179 1.4× 27 0.2× 37 0.7× 42 2.0× 4 0.3× 28 242
Gözde Gül Şahin 181 1.4× 58 0.5× 22 0.4× 19 0.9× 4 0.3× 28 242
Dimitra Gkatzia 221 1.7× 51 0.4× 10 0.2× 32 1.5× 8 0.7× 34 271

Countries citing papers authored by Maria Eskevich

Since Specialization
Citations

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

Fields of papers citing papers by Maria Eskevich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maria Eskevich

This figure shows the co-authorship network connecting the top 25 collaborators of Maria Eskevich. A scholar is included among the top collaborators of Maria Eskevich based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Maria Eskevich. Maria Eskevich is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Loading papers...

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
2026