Maha Elbayad

8 papers and 76 indexed citations i.

About

Maha Elbayad is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Industrial relations. According to data from OpenAlex, Maha Elbayad has authored 8 papers receiving a total of 76 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 0 papers in Industrial relations. Recurrent topics in Maha Elbayad’s work include Natural Language Processing Techniques (8 papers), Topic Modeling (8 papers) and Multimodal Machine Learning Applications (5 papers). Maha Elbayad is often cited by papers focused on Natural Language Processing Techniques (8 papers), Topic Modeling (8 papers) and Multimodal Machine Learning Applications (5 papers). Maha Elbayad collaborates with scholars based in United States, France and Israel. Maha Elbayad's co-authors include Jakob Verbeek, Laurent Besacier, Xutai Ma, Juan Pino, Elizabeth Salesky, Changhan Wang, Antonios Anastasopoulos, Marcello Federico, Katsuhito Sudoh and Jan Niehues and has published in prestigious journals such as Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), arXiv (Cornell University) and Repository KITopen (Karlsruhe Institute of Technology).

In The Last Decade

Co-authorship network of co-authors of Maha Elbayad i

Fields of papers citing papers by Maha Elbayad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Maha Elbayad

Since Specialization
Citations

This map shows the geographic impact of Maha Elbayad'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 Maha Elbayad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maha Elbayad 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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2025