Mohammad Mavadati

16 total papers · 409 total citations
8 papers, 276 citations indexed

About

Mohammad Mavadati is a scholar working on Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Mohammad Mavadati has authored 8 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Experimental and Cognitive Psychology, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Artificial Intelligence. Recurrent topics in Mohammad Mavadati's work include Emotion and Mood Recognition (5 papers), Face recognition and analysis (4 papers) and Face and Expression Recognition (3 papers). Mohammad Mavadati is often cited by papers focused on Emotion and Mood Recognition (5 papers), Face recognition and analysis (4 papers) and Face and Expression Recognition (3 papers). Mohammad Mavadati collaborates with scholars based in United States and Iran. Mohammad Mavadati's co-authors include Daniel McDuff, Rana el Kaliouby, Mohammad H. Mahoor, Ahmed Ghoneim and Mohamed Ashraf and has published in prestigious journals such as SHILAP Revista de lepidopterología and 2022 IEEE International Conference on Image Processing (ICIP).

In The Last Decade

Mohammad Mavadati

6 papers receiving 255 citations

Author Peers

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

Author Last Decade Papers Cites
Mohammad Mavadati 141 92 92 84 55 8 276
Agata Kołakowska 159 1.1× 39 0.4× 92 1.0× 67 0.8× 67 1.2× 23 323
Margaret McRorie 157 1.1× 51 0.6× 82 0.9× 114 1.4× 63 1.1× 13 273
Elizabeth A. Crane 109 0.8× 61 0.7× 81 0.9× 142 1.7× 17 0.3× 10 294
Ben Meuleman 129 0.9× 26 0.3× 102 1.1× 109 1.3× 27 0.5× 12 256
Claire L. Roether 89 0.6× 80 0.9× 113 1.2× 121 1.4× 19 0.3× 5 265
Nikhil Churamani 94 0.7× 104 1.1× 43 0.5× 137 1.6× 124 2.3× 19 298
Ishaan Grover 31 0.2× 69 0.8× 47 0.5× 66 0.8× 110 2.0× 6 298
Philippe Zimmermann 137 1.0× 19 0.2× 87 0.9× 82 1.0× 27 0.5× 10 267
Xunbing Shen 99 0.7× 62 0.7× 75 0.8× 51 0.6× 24 0.4× 21 187
Björn Browatzki 51 0.4× 82 0.9× 122 1.3× 44 0.5× 37 0.7× 6 319

Countries citing papers authored by Mohammad Mavadati

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Mavadati

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Mavadati

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Mavadati. A scholar is included among the top collaborators of Mohammad Mavadati 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 Mohammad Mavadati. Mohammad Mavadati is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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