World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
78
Citations
32585
World Ranking
1172
National Ranking
621

Electronics and Electrical Engineering

D-Index
75
Citations
31343
World Ranking
664
National Ranking
295

Research.com Recognitions

  • 2000 - IEEE Fellow For the statistical analysis of subspace algorithms for harmonic retrieval.

Overview

Bhaskar D. Rao is affiliated with the University of California, San Diego in the United States. Their research output mainly spans the fields of Engineering and Computer Science, with a focus on subfields such as Electrical and Electronic Engineering, Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, and Computer Networks and Communications.

The principal topics addressed in their work include:

  • Advanced MIMO Systems Optimization
  • Sparse and Compressive Sensing Techniques
  • Direction-of-Arrival Estimation Techniques
  • Blind Source Separation Techniques
  • Wireless Communication Networks Research
  • Advanced Wireless Network Optimization
  • Image and Signal Denoising Methods

Bhaskar D. Rao has published extensively in the following venues:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Wireless Communications
  • Proceedings of the National Academy of Sciences
  • IEEE Signal Processing Letters

Selected recent papers include:

  • "RE-MIMO: Recurrent and Permutation Equivariant Neural MIMO Detection", 2020, IEEE Transactions on Signal Processing
  • "Maximum Likelihood-Based Gridless DoA Estimation Using Structured Covariance Matrix Recovery and SBL With Grid Refinement", 2023, IEEE Transactions on Signal Processing
  • "Block-Sparse Signal Recovery via General Total Variation Regularized Sparse Bayesian Learning", 2022, IEEE Transactions on Signal Processing
  • "Functional connectome fingerprinting using shallow feedforward neural networks", 2021, Proceedings of the National Academy of Sciences
  • "Modified Vector Quantization for Small-Cell Access Point Placement With Inter-Cell Interference", 2022, IEEE Transactions on Wireless Communications

The frequent coauthors collaborating with Bhaskar D. Rao are:

  • Govind R. Gopal
  • Rohan R. Pote
  • Gabriel Porto Villardi
  • Aditya Sant
  • Markus Leinonen

Bhaskar D. Rao was recognized as an IEEE Fellow in 2000 for contributions related to statistical analysis of subspace algorithms for harmonic retrieval.

Best Publications

  • Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm

    I.F. Gorodnitsky;B.D. Rao

  • An overview of limited feedback in wireless communication systems

    D.J. Love;R.W. Heath;V.K.N. Lau;D. Gesbert

  • Sparse solutions to linear inverse problems with multiple measurement vectors

    S.F. Cotter;B.D. Rao;Kjersti Engan;K. Kreutz-Delgado

  • Sparse Bayesian learning for basis selection

    D.P. Wipf;B.D. Rao

  • Performance analysis of Root-Music

    B.D. Rao;K.V.S. Hari

  • Dictionary learning algorithms for sparse representation

    Kenneth Kreutz-Delgado;Joseph F. Murray;Bhaskar D. Rao;Kjersti Engan

  • An Empirical Bayesian Strategy for Solving the Simultaneous Sparse Approximation Problem

    D.P. Wipf;B.D. Rao

  • Sparse Signal Recovery With Temporally Correlated Source Vectors Using Sparse Bayesian Learning

    Zhilin Zhang;B. D. Rao

  • Sparse channel estimation via matching pursuit with application to equalization

    S.F. Cotter;B.D. Rao

  • Towards robust automatic traffic scene analysis in real-time

    D. Koller;J. Weber;T. Huang;J. Malik

  • Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm

    Irina F. Gorodnitsky;John S. George;Bhaskar D. Rao

  • Precoding and Power Optimization in Cell-Free Massive MIMO Systems

    Elina Nayebi;Alexei Ashikhmin;Thomas L. Marzetta;Hong Yang

  • An affine scaling methodology for best basis selection

    B.D. Rao;K. Kreutz-Delgado

  • Extension of SBL Algorithms for the Recovery of Block Sparse Signals With Intra-Block Correlation

    Zhilin Zhang;B. D. Rao

  • Subset selection in noise based on diversity measure minimization

    B.D. Rao;K. Engan;S.F. Cotter;J. Palmer

  • Wavefront Array Processor: Language, Architecture, and Applications

    Sun-Yuan Kung;Arun;Gal-Ezer;Bhaskar Rao

  • Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG Via Block Sparse Bayesian Learning

    Zhilin Zhang;Tzyy-Ping Jung;S. Makeig;B. D. Rao

  • Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning

    J.C. McCall;D.P. Wipf;M.M. Trivedi;B.D. Rao

  • Transmit beamforming in multiple-antenna systems with finite rate feedback: a VQ-based approach

    J.C. Roh;B.D. Rao

  • Compressed Sensing for Wireless Communications: Useful Tips and Tricks

    Jun Won Choi;Byonghyo Shim;Yacong Ding;Bhaskar Rao

  • Latent Variable Bayesian Models for Promoting Sparsity

    D. P. Wipf;B. D. Rao;S. Nagarajan

Frequent Co-Authors

Kenneth Kreutz-Delgado
Kenneth Kreutz-Delgado University of California, San Diego
Mohan M. Trivedi
Mohan M. Trivedi University of California, San Diego
David Wipf
David Wipf Amazon (United States)
Chee Wei Tan
Chee Wei Tan Nanyang Technological University
Scott Makeig
Scott Makeig University of California, San Diego
Tzyy-Ping Jung
Tzyy-Ping Jung University of California, San Diego
Truong Q. Nguyen
Truong Q. Nguyen University of California, San Diego
Thomas T. Liu
Thomas T. Liu University of California, San Diego
Michele Zorzi
Michele Zorzi University of Padua
John G. Proakis
John G. Proakis Northeastern University

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