Farzad Parvaresh

1.3k citations
50 papers · 758 · h-index 11

Impact in

Papers in

Farzad Parvaresh

47 papers receiving 723 citations

Peers

Farzad Parvaresh
Comparison fields: 5 of 53
  • Computational Mechanics 410
  • Signal Processing 182
  • Computer Vision and Pattern Recognition 145
  • Computer Networks and Communications 148
  • Acoustics and Ultrasonics 5
Replace João F. C. Mota with:
João F. C. Mota United Kingdom
Daniele Angelosante Italy
Wenbo Xu China
Guangwu Xu United States
Lizhi Cheng China
Xinggan Zhang China
Thakshila Wimalajeewa United States
Masahiro Yukawa Japan
P.M. Chau United States
Kiryung Lee United States
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Citations per field
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Citations per year

Countries citing papers authored by Farzad Parvaresh

Since Specialization
Citations

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

Fields of papers citing papers by Farzad Parvaresh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Farzad Parvaresh, 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 Farzad Parvaresh Line = papers co-authored together Farzad Parvaresh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009283
2 2008128
3 200590
4 201024
5 202223
6 200323
7 201821
8 201819
9 200816
10 201911
11 201410
12 200710
13 20128
14 20147
15 20116
16 20176
17 20225
18 20245
19
Algebraic list -decoding of error -correcting codes
20074
20 20214

About Farzad Parvaresh

Farzad Parvaresh is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Artificial Intelligence, Computational Mechanics and Signal Processing, having authored 50 papers that have together received 758 indexed citations. Recurring topics across this work include Cooperative Communication and Network Coding (16 papers), Coding theory and cryptography (8 papers), graph theory and CDMA systems (8 papers), Full-Duplex Wireless Communications (7 papers), Wireless Communication Security Techniques (7 papers), Sparse and Compressive Sensing Techniques (6 papers), Blind Source Separation Techniques (5 papers) and Power Systems Fault Detection (5 papers). The work is most often cited by research in Computational Mechanics (410 citations), Signal Processing (182 citations), Computer Vision and Pattern Recognition (145 citations), Computer Networks and Communications (148 citations) and Acoustics and Ultrasonics (5 citations). Farzad Parvaresh has collaborated with scholars based in Iran, United States and India. Frequent co-authors include Babak Hassibi, Mihailo Stojnic, Alexander Vardy, Haris Vikalo, Sidhant Misra, Raúl Etkin, Seyed M. Madani, Mehdi Gholipour, S. Mohammad Shahrtash and Ilan Shomorony. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Instrumentation and Measurement, IEEE Communications Letters, Wireless Networks and IET Generation Transmission & Distribution.

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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