Ali Pezeshki

2.6k total citations · 1 hit paper
95 papers, 1.7k citations indexed

About

Ali Pezeshki is a scholar working on Signal Processing, Computer Networks and Communications and Computational Mechanics. According to data from OpenAlex, Ali Pezeshki has authored 95 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Signal Processing, 30 papers in Computer Networks and Communications and 27 papers in Computational Mechanics. Recurrent topics in Ali Pezeshki's work include Sparse and Compressive Sensing Techniques (21 papers), Direction-of-Arrival Estimation Techniques (19 papers) and Radar Systems and Signal Processing (18 papers). Ali Pezeshki is often cited by papers focused on Sparse and Compressive Sensing Techniques (21 papers), Direction-of-Arrival Estimation Techniques (19 papers) and Radar Systems and Signal Processing (18 papers). Ali Pezeshki collaborates with scholars based in United States, Australia and Sweden. Ali Pezeshki's co-authors include Louis L. Scharf, Yuejie Chi, A.R. Calderbank, Howard Caygill, William Moran, M.R. Azimi-Sadjadi, A. Robert Calderbank, Robert Calderbank, Edwin K. P. Chong and Robert Calderbank and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Information Theory and IEEE Transactions on Signal Processing.

In The Last Decade

Ali Pezeshki

92 papers receiving 1.6k citations

Hit Papers

Sensitivity to Basis Mismatch in Compressed Sensing 2011 2026 2016 2021 2011 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ali Pezeshki United States 17 645 644 516 399 388 95 1.7k
Shane F. Cotter United States 14 1.0k 1.6× 1.3k 2.0× 284 0.6× 514 1.3× 443 1.1× 24 2.1k
Siliang Wu China 25 907 1.4× 272 0.4× 896 1.7× 635 1.6× 204 0.5× 156 1.9k
Ian K. Proudler United Kingdom 21 842 1.3× 668 1.0× 406 0.8× 369 0.9× 131 0.3× 124 1.6k
Zai Yang China 19 1.6k 2.4× 1.1k 1.6× 826 1.6× 856 2.1× 415 1.1× 71 2.7k
Parikshit Shah United States 12 445 0.7× 647 1.0× 279 0.5× 206 0.5× 262 0.7× 37 1.4k
Badri Narayan Bhaskar United States 9 671 1.0× 893 1.4× 368 0.7× 290 0.7× 369 1.0× 12 1.5k
Yngve Selén Sweden 18 629 1.0× 352 0.5× 496 1.0× 1.0k 2.6× 191 0.5× 38 2.4k
J.S. Goldstein United States 17 1.3k 2.0× 757 1.2× 1.3k 2.4× 531 1.3× 159 0.4× 95 2.3k
Zijing Zhang China 28 750 1.2× 229 0.4× 1.7k 3.3× 414 1.0× 396 1.0× 137 2.3k
Peter J. Schreier Germany 19 1.0k 1.6× 491 0.8× 338 0.7× 857 2.1× 102 0.3× 105 2.4k

Countries citing papers authored by Ali Pezeshki

Since Specialization
Citations

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

Fields of papers citing papers by Ali Pezeshki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Pezeshki

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

All Works

20 of 20 papers shown
2.
Field, Jeffrey J., et al.. (2023). Super-resolution computational saturated absorption microscopy. Journal of the Optical Society of America A. 40(7). 1409–1409. 1 indexed citations
3.
Mishra, Kumar Vijay, Samuel Pinilla, Ali Pezeshki, & A.R. Calderbank. (2022). Group-Theoretic Wideband Radar Waveform Design. 2022 IEEE International Symposium on Information Theory (ISIT). 1821–1825. 2 indexed citations
4.
Field, Jeffrey J., et al.. (2022). Tomographic single pixel spatial frequency projection imaging. Optics Communications. 520. 128401–128401. 12 indexed citations
5.
Liu, Yajing, Edwin K. P. Chong, Ali Pezeshki, & Zhenliang Zhang. (2020). Submodular optimization problems and greedy strategies: A survey. Discrete Event Dynamic Systems. 30(3). 381–412. 6 indexed citations
6.
Liu, Yajing, Zhenliang Zhang, Edwin K. P. Chong, & Ali Pezeshki. (2018). Performance Bounds with Curvature for Batched Greedy Optimization. Journal of Optimization Theory and Applications. 177(2). 535–562. 2 indexed citations
7.
Liu, Yajing, Edwin K. P. Chong, & Ali Pezeshki. (2017). Performance bounds for Nash equilibria in submodular utility systems with user groups. Journal of Control and Decision. 5(1). 1–18. 1 indexed citations
8.
Mohammadi‐Ghalehbin, Behnam, et al.. (2015). Frequency of Trichomonas Vaginalis Infection among Pregnant Women Referred to Health and Medical Centers in Ardabil City, 2013-2014. SHILAP Revista de lepidopterología. 15(1). 75–82. 1 indexed citations
9.
Zhang, Zhenliang, Edwin K. P. Chong, Ali Pezeshki, & William Moran. (2013). Near Optimality of Greedy Strategies for String Submodular Functions with Forward and Backward Curvature Constraints. arXiv (Cornell University). 1 indexed citations
10.
Zhang, Zhenliang, Edwin K. P. Chong, Ali Pezeshki, William Moran, & Howard Caygill. (2013). Learning in Hierarchical Social Networks. IEEE Journal of Selected Topics in Signal Processing. 7(2). 305–317. 8 indexed citations
11.
Zhang, Zhenliang, T.C.E. Cheng, Ali Pezeshki, William Moran, & Howard Caygill. (2013). Detection Performance in Balanced Binary Relay Trees With Node and Link Failures. IEEE Transactions on Signal Processing. 61(9). 2165–2177. 9 indexed citations
12.
Chong, Edwin K. P., et al.. (2012). Adaptive compressive sampling using partially observable markov decision processes. 5269–5272. 3 indexed citations
13.
Calderbank, Robert, et al.. (2010). Sparse fusion frames: existence and construction. Advances in Computational Mathematics. 35(1). 1–31. 24 indexed citations
14.
Chi, Yuejie, et al.. (2009). Sensitivity to basis mismatch of compressed sensing for spectrum analysis and beamforming. 13 indexed citations
15.
Kutyniok, Gitta, Ali Pezeshki, Robert Calderbank, & Can Liu. (2008). Robust dimension reduction, fusion frames, and Grassmannian packings. Applied and Computational Harmonic Analysis. 26(1). 64–76. 44 indexed citations
16.
Pezeshki, Ali, B.D. Van Veen, Louis L. Scharf, Henry Cox, & Magnus Lundberg Nordenvaad. (2008). Eigenvalue Beamforming Using a Multirank MVDR Beamformer and Subspace Selection. IEEE Transactions on Signal Processing. 56(5). 1954–1967. 64 indexed citations
17.
Pezeshki, Ali, M.R. Azimi-Sadjadi, & Louis L. Scharf. (2007). Undersea Target Classification Using Canonical Correlation Analysis. IEEE Journal of Oceanic Engineering. 32(4). 948–955. 42 indexed citations
18.
Calderbank, A.R., Howard Caygill, William Moran, Ali Pezeshki, & M.D. Zoltowski. (2006). Instantaneous Radar Polarimetry with Multiple Dually-polarized Antennas. 757–761. 10 indexed citations
19.
Scharf, Louis L. & Ali Pezeshki. (2006). Virtual Array Processing for Active Radar and Sonar Sensing. 1. 740–744. 2 indexed citations
20.
Pezeshki, Ali, M.R. Azimi-Sadjadi, & Louis L. Scharf. (2003). A network for recursive extraction of canonical coordinates. Neural Networks. 16(5-6). 801–808. 11 indexed citations

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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