Soheil Feizi

240 total papers · 10.4k total citations
69 papers, 1.3k citations indexed

About

Soheil Feizi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Soheil Feizi has authored 69 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 19 papers in Computer Vision and Pattern Recognition and 18 papers in Electrical and Electronic Engineering. Recurrent topics in Soheil Feizi's work include Adversarial Robustness in Machine Learning (18 papers), Cooperative Communication and Network Coding (9 papers) and Anomaly Detection Techniques and Applications (9 papers). Soheil Feizi is often cited by papers focused on Adversarial Robustness in Machine Learning (18 papers), Cooperative Communication and Network Coding (9 papers) and Anomaly Detection Techniques and Applications (9 papers). Soheil Feizi collaborates with scholars based in United States, Iran and Canada. Soheil Feizi's co-authors include Muriel Médard, Manolis Kellis, Daniel Marbach, Xiaolan Zhang, Peter Rogov, Tarjei S. Mikkelsen, Curtis G. Callan, Tiberiu Teşileanu, Eric S. Lander and Anand Murugan and has published in prestigious journals such as Nature Biotechnology, Scientific Reports and IEEE Transactions on Information Theory.

In The Last Decade

Soheil Feizi

62 papers receiving 1.3k citations

Author Peers

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

Author Last Decade Papers Cites
Soheil Feizi 592 280 184 183 176 69 1.3k
Alioune Ngom 537 0.9× 253 0.9× 146 0.8× 123 0.7× 72 0.4× 90 1.2k
Ying Xu 315 0.5× 408 1.5× 165 0.9× 150 0.8× 73 0.4× 109 1.5k
Shu Wang 431 0.7× 221 0.8× 76 0.4× 293 1.6× 133 0.8× 114 1.4k
Raj Acharya 421 0.7× 145 0.5× 407 2.2× 221 1.2× 190 1.1× 132 1.4k
Seunghyun Park 572 1.0× 243 0.9× 185 1.0× 87 0.5× 183 1.0× 77 1.7k
Heinz Koeppl 880 1.5× 123 0.4× 46 0.3× 163 0.9× 150 0.9× 150 1.5k
Stefan C. Kremer 281 0.5× 485 1.7× 157 0.9× 166 0.9× 152 0.9× 66 1.3k
Shankar Vembu 343 0.6× 365 1.3× 179 1.0× 162 0.9× 407 2.3× 24 1.5k
Pierre Dupont 488 0.8× 462 1.6× 184 1.0× 86 0.5× 24 0.1× 92 1.5k
Mario Rosario Guarracino 560 0.9× 186 0.7× 122 0.7× 97 0.5× 29 0.2× 105 1.3k

Countries citing papers authored by Soheil Feizi

Since Specialization
Citations

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

Fields of papers citing papers by Soheil Feizi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Soheil Feizi

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