Amir Zadeh

80 total papers · 7.5k total citations
29 papers, 3.9k citations indexed

About

Amir Zadeh is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology. According to data from OpenAlex, Amir Zadeh has authored 29 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 6 papers in Experimental and Cognitive Psychology. Recurrent topics in Amir Zadeh's work include Multimodal Machine Learning Applications (11 papers), Topic Modeling (8 papers) and Sentiment Analysis and Opinion Mining (6 papers). Amir Zadeh is often cited by papers focused on Multimodal Machine Learning Applications (11 papers), Topic Modeling (8 papers) and Sentiment Analysis and Opinion Mining (6 papers). Amir Zadeh collaborates with scholars based in United States, Singapore and Mexico. Amir Zadeh's co-authors include Louis–Philippe Morency, Tadas Baltrušaitis, Yao Chong Lim, Soujanya Poria, Erik Cambria, Paul Pu Liang, Devamanyu Hazarika, Eli Pincus, Rowan Zellers and Navonil Majumder and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACM Computing Surveys and Information Fusion.

In The Last Decade

Amir Zadeh

29 papers receiving 3.7k citations

Hit Papers

OpenFace 2.0: Facial Beha... 2016 2026 2019 2022 2018 2017 2018 2016 2019 250 500 750 1000

Author Peers

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

Author Last Decade Papers Cites
Amir Zadeh 2.4k 1.6k 1.1k 581 502 29 3.9k
Abe Kazemzadeh 2.2k 0.9× 2.5k 1.6× 650 0.6× 1.5k 2.6× 465 0.9× 36 3.9k
Murtaza Bulut 1.7k 0.7× 2.4k 1.5× 687 0.6× 1.5k 2.5× 461 0.9× 26 3.4k
Martin Wöllmer 2.6k 1.1× 2.6k 1.6× 965 0.8× 2.2k 3.8× 819 1.6× 81 5.0k
Nicolas Tsapatsoulis 779 0.3× 1.3k 0.8× 1.1k 0.9× 756 1.3× 388 0.8× 109 2.7k
Paul Pu Liang 2.6k 1.1× 1.0k 0.7× 910 0.8× 587 1.0× 188 0.4× 47 3.4k
Ellen Douglas‐Cowie 1.3k 0.5× 2.8k 1.7× 864 0.8× 1.3k 2.3× 851 1.7× 57 3.8k
Ashish Kapoor 1.8k 0.8× 564 0.4× 1.6k 1.4× 233 0.4× 390 0.8× 96 4.0k
Devamanyu Hazarika 3.2k 1.4× 1.1k 0.7× 774 0.7× 484 0.8× 311 0.6× 30 4.6k
Laurence Devillers 1.9k 0.8× 2.2k 1.4× 510 0.4× 1.5k 2.5× 628 1.3× 99 3.6k
Felix Weninger 2.2k 0.9× 1.4k 0.9× 657 0.6× 2.4k 4.2× 348 0.7× 100 4.2k

Countries citing papers authored by Amir Zadeh

Since Specialization
Citations

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

Fields of papers citing papers by Amir Zadeh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amir Zadeh

This figure shows the co-authorship network connecting the top 25 collaborators of Amir Zadeh. A scholar is included among the top collaborators of Amir Zadeh 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 Amir Zadeh. Amir Zadeh 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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