D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 74 Citations 26,366 484 World Ranking 610 National Ranking 10

Research.com Recognitions

Awards & Achievements

2016 - IEEE Kiyo Tomiyasu Award “For development of the theory and implementation of sub-Nyquist sampling with applications to radar, communications, and ultrasound.”

2013 - IEEE Fellow For contributions to compressed sampling, generalized sampling, and convex optimization

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Statistics
  • Quantum mechanics

Her scientific interests lie mostly in Algorithm, Compressed sensing, Mathematical optimization, Signal processing and Signal reconstruction. Yonina C. Eldar has included themes like Subspace topology, Sampling, Signal, Phase retrieval and Convex optimization in her Algorithm study. Her Compressed sensing research is multidisciplinary, incorporating perspectives in Sampling, Sparse matrix, Sparse approximation, Bandwidth and Iterative reconstruction.

Her Bandwidth research includes elements of Nyquist rate, Wideband and Nyquist–Shannon sampling theorem. She studied Mathematical optimization and Mean squared error that intersect with Estimation of covariance matrices. Yonina C. Eldar has researched Signal processing in several fields, including Continuous signal, Analog signal, Robustness, Artificial intelligence and Pattern recognition.

Her most cited work include:

  • Compressed sensing : theory and applications (1555 citations)
  • From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals (953 citations)
  • Block-Sparse Signals: Uncertainty Relations and Efficient Recovery (920 citations)

What are the main themes of her work throughout her whole career to date?

Her primary areas of investigation include Algorithm, Compressed sensing, Mathematical optimization, Artificial intelligence and Electronic engineering. While the research belongs to areas of Algorithm, Yonina C. Eldar spends her time largely on the problem of Sampling, intersecting her research to questions surrounding Nyquist–Shannon sampling theorem. The concepts of her Compressed sensing study are interwoven with issues in Matrix, Beamforming, Sparse approximation and Analog signal.

Her biological study spans a wide range of topics, including Mean squared error, Estimator, Applied mathematics and Convex optimization. Her Artificial intelligence study integrates concerns from other disciplines, such as Ultrasound, Computer vision and Pattern recognition. Her research integrates issues of Radar and MIMO in her study of Electronic engineering.

She most often published in these fields:

  • Algorithm (37.39%)
  • Compressed sensing (18.89%)
  • Mathematical optimization (17.80%)

What were the highlights of her more recent work (between 2019-2021)?

  • Algorithm (37.39%)
  • Artificial intelligence (16.02%)
  • Deep learning (5.64%)

In recent papers she was focusing on the following fields of study:

Her scientific interests lie mostly in Algorithm, Artificial intelligence, Deep learning, Communication channel and Radar. Her Algorithm research focuses on Compressed sensing in particular. Her study in Artificial intelligence is interdisciplinary in nature, drawing from both Beamforming, Computer vision and Pattern recognition.

Her Deep learning study also includes fields such as

  • Temporal resolution which connect with Super-resolution microscopy,
  • Microscopy, which have a strong connection to Ultrasound. Her research in Communication channel intersects with topics in Wireless, Telecommunications link and Detector. Her Radar research integrates issues from Computer hardware, Modulation, Waveform, Communications system and Electronic engineering.

Between 2019 and 2021, her most popular works were:

  • Deep Learning in Ultrasound Imaging (59 citations)
  • Deep Unfolded Robust PCA With Application to Clutter Suppression in Ultrasound (49 citations)
  • ViterbiNet: A Deep Learning Based Viterbi Algorithm for Symbol Detection (36 citations)

In her most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Statistics
  • Quantum mechanics

Yonina C. Eldar spends much of her time researching Algorithm, Artificial intelligence, MIMO, Deep learning and Communication channel. Her Algorithm study combines topics from a wide range of disciplines, such as Graphical model, Graph, Graph and Signal processing. Her Artificial intelligence research is multidisciplinary, relying on both Ultrasound and Ultrasound imaging.

Her studies deal with areas such as Electronic circuit, Analog signal, Reduction, Baseband and Electronic engineering as well as MIMO. Her Electronic engineering research includes elements of Radar, Wireless network, Spectral bands and Compressed sensing. Her Compressed sensing research is multidisciplinary, incorporating elements of Waveform, Narrowband and Antenna.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Compressed sensing : theory and applications

Yonina C. Eldar;Gitta Kutyniok.
Published in <b>2012</b> in Cambridge New York by Cambridge University Press (2012)

2394 Citations

Block-Sparse Signals: Uncertainty Relations and Efficient Recovery

Yonina C Eldar;Patrick Kuppinger;Helmut Bolcskei.
IEEE Transactions on Signal Processing (2010)

1310 Citations

From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals

M. Mishali;Y.C. Eldar.
IEEE Journal of Selected Topics in Signal Processing (2010)

1270 Citations

Structured Compressed Sensing: From Theory to Applications

M. F. Duarte;Y. C. Eldar.
IEEE Transactions on Signal Processing (2011)

1047 Citations

Robust Recovery of Signals From a Structured Union of Subspaces

Y.C. Eldar;M. Mishali.
IEEE Transactions on Information Theory (2009)

1043 Citations

Compressed Sensing: List of contributors

Yonina C. Eldar;Gitta Kutyniok.
(2012)

993 Citations

Linear precoding via conic optimization for fixed MIMO receivers

A. Wiesel;Y.C. Eldar;S. Shamai.
IEEE Transactions on Signal Processing (2006)

907 Citations

Blind Multiband Signal Reconstruction: Compressed Sensing for Analog Signals

M. Mishali;Y.C. Eldar.
IEEE Transactions on Signal Processing (2009)

891 Citations

Compressed sensing with coherent and redundant dictionaries

Emmanuel J. Candès;Yonina C. Eldar;Deanna Needell;Paige Randall.
Applied and Computational Harmonic Analysis (2011)

863 Citations

A probabilistic Hough transform

N. Kiryati;Y. Eldar;A. M. Bruckstein.
Pattern Recognition (1991)

846 Citations

Best Scientists Citing Yonina C. Eldar

Bjorn Ottersten

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Richard G. Baraniuk

Richard G. Baraniuk

Rice University

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Babak Hassibi

Babak Hassibi

California Institute of Technology

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Angshul Majumdar

Angshul Majumdar

Indraprastha Institute of Information Technology Delhi

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Geert Leus

Geert Leus

Delft University of Technology

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Bhaskar D. Rao

Bhaskar D. Rao

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Holger Boche

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Markku Juntti

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University of Oulu

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Moeness G. Amin

Moeness G. Amin

Villanova University

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Raja Giryes

Raja Giryes

Tel Aviv University

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Marco F. Duarte

Marco F. Duarte

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Volkan Cevher

Volkan Cevher

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Antti Tolli

Antti Tolli

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Jinho Choi

Jinho Choi

Deakin University

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Georgios B. Giannakis

Georgios B. Giannakis

University of Minnesota

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Gitta Kutyniok

Gitta Kutyniok

Ludwig-Maximilians-Universität München

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Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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