Armin Eftekhari

31 papers receiving 284 citations

Peers

Armin Eftekhari
Comparison fields: 5 of 65
  • Computational Mechanics 152
  • Computational Mathematics 4
  • Computer Vision and Pattern Recognition 112
  • Signal Processing 48
  • Acoustics and Ultrasonics 2
Replace Goran Marjanovic with:
Goran Marjanovic Australia
Xinyue Shen China
Yohann de Castro France
Zhang Liu China
Russell Trahan United States
Mariette Annergren Sweden
Ivars Bilinskis Latvia
J. Schroeder United States
Argyrios Zymnis United States
Armin Eftekhari relative to Goran Marjanovic Australia Goran Marjanovic's profile →
Citations per field
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Citations per year

Countries citing papers authored by Armin Eftekhari

Since Specialization
Citations

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

Fields of papers citing papers by Armin Eftekhari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Armin Eftekhari, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Armin Eftekhari Line = papers co-authored together Armin Eftekhari links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201435
2 201134
3 200934
4 201130
5 201725
6 201023
7 201022
8 199214
9 201811
10
Fast and Provable ADMM for Learning with Generative Priors
20197
11 20197
12
20186
13 20136
14 20195
15 20094
16 20084
17 20233
18 20093
19 20163
20 20203

About Armin Eftekhari

Armin Eftekhari is a scholar working on Computational Mechanics, Computer Vision and Pattern Recognition, Signal Processing, Biomedical Engineering and Artificial Intelligence, having authored 33 papers that have together received 300 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (17 papers), Image and Signal Denoising Methods (7 papers), Blind Source Separation Techniques (6 papers), Face and Expression Recognition (5 papers), Microwave Imaging and Scattering Analysis (5 papers), Medical Image Segmentation Techniques (4 papers), Advanced Image Processing Techniques (3 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Computational Mechanics (152 citations), Computational Mathematics (4 citations), Computer Vision and Pattern Recognition (112 citations), Signal Processing (48 citations) and Acoustics and Ultrasonics (2 citations). Armin Eftekhari has collaborated with scholars based in United States, Iran and United Kingdom. Frequent co-authors include Michael B. Wakin, Hamid Abrishami Moghaddam, Massoud Babaie‐Zadeh, Javad Alirezaie, Christopher J. Rozell, Christian Jutten, R. Viswanathan, Armen Kocharian, Mohamad Forouzanfar and Rachel Ward. Their work appears in journals such as SIAM Journal on Optimization, Applied and Computational Harmonic Analysis, Information and Inference A Journal of the IMA, International Journal of Computer Assisted Radiology and Surgery and Statistics and Computing.

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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