What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Algorithm
Bhaskar D. Rao spends much of his time researching Algorithm, Artificial intelligence, Signal processing, Mathematical optimization and Bayesian inference.
His work deals with themes such as Mean squared error and White noise, which intersect with Algorithm.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Computer vision and Pattern recognition.
Many of his research projects under Signal processing are closely connected to Systolic array with Systolic array, tying the diverse disciplines of science together.
His primary area of study in Mathematical optimization is in the field of Iterative method.
His Bayesian inference research includes elements of Sparse approximation, Relevance and Maximum a posteriori estimation.
His most cited work include:
- Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm (1476 citations)
- An overview of limited feedback in wireless communication systems (1353 citations)
- Sparse solutions to linear inverse problems with multiple measurement vectors (1165 citations)
What are the main themes of his work throughout his whole career to date?
Bhaskar D. Rao mainly investigates Algorithm, Communication channel, Artificial intelligence, Mathematical optimization and Control theory.
Bhaskar D. Rao has researched Algorithm in several fields, including MIMO, Speech recognition and Signal processing.
His studies in Communication channel integrate themes in fields like Transmitter and Electronic engineering.
His Artificial intelligence research incorporates elements of Machine learning, Computer vision and Pattern recognition.
His study in Mathematical optimization is interdisciplinary in nature, drawing from both Scheduling and Applied mathematics.
His work focuses on many connections between Control theory and other disciplines, such as Beamforming, that overlap with his field of interest in Power control and Iterative method.
He most often published in these fields:
- Algorithm (37.48%)
- Communication channel (21.50%)
- Artificial intelligence (18.54%)
What were the highlights of his more recent work (between 2013-2021)?
- Algorithm (37.48%)
- Bayesian inference (10.65%)
- Artificial intelligence (18.54%)
In recent papers he was focusing on the following fields of study:
Bhaskar D. Rao focuses on Algorithm, Bayesian inference, Artificial intelligence, Communication channel and Pattern recognition.
The various areas that he examines in his Algorithm study include MIMO and Sparse matrix.
His biological study spans a wide range of topics, including Prior probability, Point estimation, Expectation–maximization algorithm, Kalman filter and Signal.
His research investigates the connection between Artificial intelligence and topics such as Machine learning that intersect with issues in K-SVD.
His Communication channel research includes themes of Wireless, Scheduling, Overhead and Mean squared error.
His Pattern recognition study integrates concerns from other disciplines, such as Speech enhancement, Range, Speech processing and Maximum a posteriori estimation.
Between 2013 and 2021, his most popular works were:
- Precoding and Power Optimization in Cell-Free Massive MIMO Systems (234 citations)
- Compressed Sensing for Wireless Communications: Useful Tips and Tricks (162 citations)
- Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning (82 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Algorithm
Bhaskar D. Rao mainly focuses on Algorithm, Artificial intelligence, Communication channel, Bayesian inference and MIMO.
Bhaskar D. Rao studies Algorithm, namely Estimation theory.
His Artificial intelligence research integrates issues from Machine learning and Pattern recognition.
His Communication channel research incorporates themes from Mean squared error, Wireless and Compressed sensing.
Bhaskar D. Rao combines subjects such as Low complexity, Message passing, Sparse approximation, Multivariate statistics and Signal with his study of Bayesian inference.
The concepts of his MIMO study are interwoven with issues in Throughput, Telecommunications link and Control theory.
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