Maryam Khademi

34 papers and 572 indexed citations i.

About

Maryam Khademi is a scholar working on Artificial Intelligence, Rehabilitation and Computer Vision and Pattern Recognition. According to data from OpenAlex, Maryam Khademi has authored 34 papers receiving a total of 572 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 9 papers in Rehabilitation and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Maryam Khademi’s work include Stroke Rehabilitation and Recovery (9 papers), Gaze Tracking and Assistive Technology (4 papers) and graph theory and CDMA systems (4 papers). Maryam Khademi is often cited by papers focused on Stroke Rehabilitation and Recovery (9 papers), Gaze Tracking and Assistive Technology (4 papers) and graph theory and CDMA systems (4 papers). Maryam Khademi collaborates with scholars based in Iran, United States and Türkiye. Maryam Khademi's co-authors include Hossein Mousavi Hondori, Cristina Videira Lopes, Lucy Dodakian, Steven C. Cramer, Alison McKenzie, Tri Huynh, Michael Maire, Simon Kornblith, Matthew R. Walter and S. H. Hendi and has published in prestigious journals such as The Astrophysical Journal, Stroke and Journal of High Energy Physics.

In The Last Decade

Co-authorship network of co-authors of Maryam Khademi i

Fields of papers citing papers by Maryam Khademi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Maryam Khademi

Since Specialization
Citations

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