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- Babak Hassibi

Discipline name
H-index
Citations
Publications
World Ranking
National Ranking

Electronics and Electrical Engineering
H-index
57
Citations
19,830
257
World Ranking
680
National Ranking
336

Computer Science
H-index
60
Citations
23,788
314
World Ranking
1504
National Ranking
838

- 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.

- 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)

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.

- Algorithm (29.31%)
- Discrete mathematics (18.18%)
- Mathematical optimization (17.24%)

- Algorithm (29.31%)
- Applied mathematics (12.07%)
- Mathematical optimization (17.24%)

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.

- 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)

- 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.

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.

How much training is needed in multiple-antenna wireless links?

B. Hassibi;B.M. Hochwald.

IEEE Transactions on Information Theory **(2003)**

2454 Citations

High-rate codes that are linear in space and time

B. Hassibi;B.M. Hochwald.

IEEE Transactions on Information Theory **(2002)**

1832 Citations

Second order derivatives for network pruning: Optimal Brain Surgeon

Babak Hassibi;David G. Stork.

neural information processing systems **(1992)**

1712 Citations

On the capacity of MIMO broadcast channels with partial side information

M. Sharif;B. Hassibi.

IEEE Transactions on Information Theory **(2005)**

1586 Citations

On the sphere-decoding algorithm I. Expected complexity

B. Hassibi;H. Vikalo.

IEEE Transactions on Signal Processing **(2005)**

1485 Citations

Distributed Space-Time Coding in Wireless Relay Networks

Y. Jing;B. Hassibi.

IEEE Transactions on Wireless Communications **(2006)**

1222 Citations

The Secrecy Capacity of the MIMO Wiretap Channel

F. Oggier;B. Hassibi.

IEEE Transactions on Information Theory **(2011)**

864 Citations

An efficient square-root algorithm for BLAST

B. Hassibi.

international conference on acoustics, speech, and signal processing **(2000)**

695 Citations

Optimal Brain Surgeon and general network pruning

B. Hassibi;D.G. Stork;G.J. Wolff.

IEEE International Conference on Neural Networks **(1993)**

602 Citations

Indefinite-quadratic estimation and control: a unified approach to H 2 and H ∞ theories

Babak Hassibi;Ali H. Sayed;Thomas Kailath.

**(1999)**

535 Citations

Profile was last updated on December 6th, 2021.

Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).

The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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