Praneeth Narayanamurthy

560 total citations · 1 hit paper
24 papers, 400 citations indexed

About

Praneeth Narayanamurthy is a scholar working on Computational Mechanics, Computer Networks and Communications and Signal Processing. According to data from OpenAlex, Praneeth Narayanamurthy has authored 24 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computational Mechanics, 9 papers in Computer Networks and Communications and 8 papers in Signal Processing. Recurrent topics in Praneeth Narayanamurthy's work include Sparse and Compressive Sensing Techniques (19 papers), Distributed Sensor Networks and Detection Algorithms (9 papers) and Blind Source Separation Techniques (7 papers). Praneeth Narayanamurthy is often cited by papers focused on Sparse and Compressive Sensing Techniques (19 papers), Distributed Sensor Networks and Detection Algorithms (9 papers) and Blind Source Separation Techniques (7 papers). Praneeth Narayanamurthy collaborates with scholars based in United States, South Korea and United Kingdom. Praneeth Narayanamurthy's co-authors include Namrata Vaswani, Thierry Bouwmans, Sajid Javed, Aditya Ramamoorthy, Shaama Mallikarjun Sharada, Selin Bac and Urbashi Mitra and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing and IEEE Signal Processing Magazine.

In The Last Decade

Praneeth Narayanamurthy

23 papers receiving 394 citations

Hit Papers

Robust Subspace Learning: Robust PCA, Robust Subspace Tra... 2018 2026 2020 2023 2018 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Robust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace Recovery
    2018 262 citations Namrata Vaswani, Thierry Bouwmans et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Praneeth Narayanamurthy United States 8 194 170 90 62 61 24 400
Dominique Pastor France 14 115 0.6× 128 0.8× 193 2.1× 80 1.3× 41 0.7× 52 462
Manqi Zhao China 10 156 0.8× 62 0.4× 49 0.5× 92 1.5× 59 1.0× 30 340
Armin Eftekhari United States 9 112 0.6× 152 0.9× 48 0.5× 36 0.6× 17 0.3× 33 300
Chenlu Qiu United States 9 153 0.8× 223 1.3× 126 1.4× 49 0.8× 21 0.3× 16 342
Hengyou Wang China 9 194 1.0× 105 0.6× 40 0.4× 74 1.2× 90 1.5× 55 316
Argyrios Zymnis United States 6 69 0.4× 194 1.1× 78 0.9× 42 0.7× 45 0.7× 11 346
Junmei Yang China 12 110 0.6× 127 0.7× 200 2.2× 82 1.3× 136 2.2× 35 601
Ender M. Ekşioğlu Türkiye 11 186 1.0× 335 2.0× 159 1.8× 41 0.7× 47 0.8× 41 567
Goran Marjanovic Australia 9 96 0.5× 184 1.1× 75 0.8× 59 1.0× 17 0.3× 19 319
Miloš Brajović Montenegro 12 157 0.8× 142 0.8× 137 1.5× 109 1.8× 16 0.3× 66 495

Countries citing papers authored by Praneeth Narayanamurthy

Since Specialization
Citations

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

Fields of papers citing papers by Praneeth Narayanamurthy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Praneeth Narayanamurthy

This figure shows the co-authorship network connecting the top 25 collaborators of Praneeth Narayanamurthy. A scholar is included among the top collaborators of Praneeth Narayanamurthy 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 Praneeth Narayanamurthy. Praneeth Narayanamurthy 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
1.
Narayanamurthy, Praneeth, et al.. (2024). Matrix Approximation With Side Information: When Column Sampling Is Enough. IEEE Transactions on Signal Processing. 72. 2276–2291. 1 indexed citations
2.
Narayanamurthy, Praneeth, et al.. (2024). Sketched Column-Based Matrix Approximation With Side Information. 9816–9820.
3.
Narayanamurthy, Praneeth, et al.. (2023). Column-Based Matrix Approximation with Quasi-Polynomial Structure. 1–5. 3 indexed citations
4.
Narayanamurthy, Praneeth, Namrata Vaswani, & Aditya Ramamoorthy. (2022). Federated Over-Air Subspace Tracking From Incomplete and Corrupted Data. IEEE Transactions on Signal Processing. 70. 3906–3920. 9 indexed citations
5.
Narayanamurthy, Praneeth, Namrata Vaswani, & Aditya Ramamoorthy. (2020). Federated Over-the-Air Subspace Learning from Incomplete Data.. arXiv (Cornell University). 1 indexed citations
6.
Narayanamurthy, Praneeth & Namrata Vaswani. (2020). Fast Robust Subspace Tracking via PCA in Sparse Data-Dependent Noise. IEEE Journal on Selected Areas in Information Theory. 1(3). 723–744. 8 indexed citations
7.
Narayanamurthy, Praneeth, et al.. (2020). Provable Low Rank Phase Retrieval. IEEE Transactions on Information Theory. 66(9). 5875–5903. 12 indexed citations
8.
Narayanamurthy, Praneeth, et al.. (2019). Phaseless PCA: Low-Rank Matrix Recovery from Column-wise Phaseless Measurements. arXiv (Cornell University). 4762–4770. 7 indexed citations
9.
Narayanamurthy, Praneeth, et al.. (2019). Provable Memory-efficient Online Robust Matrix Completion. 17. 7918–7922. 3 indexed citations
10.
Narayanamurthy, Praneeth, et al.. (2019). Provable Subspace Tracking From Missing Data and Matrix Completion. IEEE Transactions on Signal Processing. 67(16). 4245–4260. 17 indexed citations
11.
Narayanamurthy, Praneeth, et al.. (2018). Subspace Tracking from Missing and Outlier Corrupted Data.. arXiv (Cornell University). 2 indexed citations
12.
Vaswani, Namrata, Thierry Bouwmans, Sajid Javed, & Praneeth Narayanamurthy. (2018). Robust PCA and Robust Subspace Tracking: A Comparative Evaluation. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
13.
Narayanamurthy, Praneeth & Namrata Vaswani. (2018). Provable Dynamic Robust PCA or Robust Subspace Tracking. 376–380. 13 indexed citations
14.
Vaswani, Namrata & Praneeth Narayanamurthy. (2018). PCA in Sparse Data-Dependent Noise. 641–645. 7 indexed citations
15.
Narayanamurthy, Praneeth & Namrata Vaswani. (2018). A Fast and Memory-Efficient Algorithm for Robust PCA (MEROP). 4684–4688. 25 indexed citations
16.
Vaswani, Namrata, Thierry Bouwmans, Sajid Javed, & Praneeth Narayanamurthy. (2017). Robust PCA and Robust Subspace Tracking.. arXiv (Cornell University). 4 indexed citations
17.
Narayanamurthy, Praneeth & Namrata Vaswani. (2017). New Results for Provable Dynamic Robust PCA.. arXiv (Cornell University). 1 indexed citations
18.
Narayanamurthy, Praneeth & Namrata Vaswani. (2017). Nearly Optimal Robust Subspace Tracking and Dynamic Robust PCA. arXiv (Cornell University). 2 indexed citations
19.
Narayanamurthy, Praneeth & Namrata Vaswani. (2017). MEDRoP: Memory-Efficient Dynamic Robust PCA.. arXiv (Cornell University). 6 indexed citations
20.
Narayanamurthy, Praneeth & Namrata Vaswani. (2017). Nearly Optimal Robust Subspace Tracking. arXiv (Cornell University). 3698–3706. 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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