What is he best known for?
The fields of study he is best known for:
- Algorithm
- Statistics
- Algebra
Babak Hassibi focuses on Algorithm, Communication channel, Mathematical optimization, Discrete mathematics and Decoding methods.
His Algorithm study incorporates themes from Signal reconstruction, Signal processing and Convex optimization.
Babak Hassibi interconnects Transmitter, Wireless network, Computer network and Topology in the investigation of issues within Communication channel.
The study incorporates disciplines such as Wireless and Relay in addition to Topology.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Power, Adaptive filter, Applied mathematics and Rank.
The various areas that Babak Hassibi examines in his Channel capacity study include Upper and lower bounds, Data transmission and Fading.
His most cited work include:
- How much training is needed in multiple-antenna wireless links? (2045 citations)
- High-rate codes that are linear in space and time (1361 citations)
- On the capacity of MIMO broadcast channels with partial side information (1339 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Algorithm, Discrete mathematics, Mathematical optimization, Communication channel and Decoding methods.
His Algorithm study focuses on Compressed sensing in particular.
As part of the same scientific family, Babak Hassibi usually focuses on Discrete mathematics, concentrating on Upper and lower bounds and intersecting with Control theory.
His Communication channel research incorporates elements of Transmitter, Topology, Computer network and Wireless.
His studies in Computer network integrate themes in fields like Wireless network, MIMO and Relay.
The Decoding methods study combines topics in areas such as Computational complexity theory and Theoretical computer science.
He most often published in these fields:
- Algorithm (29.31%)
- Discrete mathematics (18.18%)
- Mathematical optimization (17.24%)
What were the highlights of his more recent work (between 2015-2021)?
- Algorithm (29.31%)
- Applied mathematics (12.07%)
- Mathematical optimization (17.24%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Algorithm, Applied mathematics, Mathematical optimization, Discrete mathematics and Control theory.
He mostly deals with Decoding methods in his studies of Algorithm.
His Mathematical optimization research is multidisciplinary, incorporating elements of Kalman filter and Regret.
His research integrates issues of Matrix, Generator matrix and Combinatorics in his study of Discrete mathematics.
His Control theory research focuses on subjects like Upper and lower bounds, which are linked to Markov chain.
Babak Hassibi has researched Communication channel in several fields, including Transmitter, Transmitter power output, Encoder and Quantization.
Between 2015 and 2021, his most popular works were:
- Improving Distributed Gradient Descent Using Reed-Solomon Codes (119 citations)
- STFT Phase Retrieval: Uniqueness Guarantees and Recovery Algorithms (85 citations)
- Precise Error Analysis of Regularized $M$ -Estimators in High Dimensions (75 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Algorithm
- Algebra
Babak Hassibi spends much of his time researching Algorithm, Decoding methods, Applied mathematics, Mathematical optimization and Gaussian.
His study in Algorithm is interdisciplinary in nature, drawing from both Projection, Minimum mean square error, Linear-quadratic-Gaussian control, Discrete Fourier transform and Aperiodic graph.
In his study, Noise measurement, Lasso, Modulation and Word error rate is strongly linked to Bounded function, which falls under the umbrella field of Decoding methods.
His Gaussian research incorporates themes from Quantization, Mean squared error, MIMO, Estimator and Signal processing.
His research investigates the connection between Quantization and topics such as Sampling that intersect with problems in Communication channel.
Combinatorics is closely connected to Compressed sensing in his research, which is encompassed under the umbrella topic of Mean squared error.
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