H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering H-index 90 Citations 50,160 305 World Ranking 79 National Ranking 45
Computer Science H-index 91 Citations 46,702 339 World Ranking 235 National Ranking 141

Research.com Recognitions

Awards & Achievements

2018 - Fellow of the American Mathematical Society For contributions to information theory and related areas, and for applications.

2012 - US President's National Medal of Science "For transformative contributions to the fields of information and system science, for distinctive and sustained mentoring of young scholars, and for translation of scientific ideas into entrepreneurial ventures that have had a significant impact on industry.", Award presented by President Barack Obama at a ceremony in the East Room of the White House on November 20, 2014.

2009 - BBVA Foundation Frontiers of Knowledge Award

2009 - Fellow of the Royal Society, United Kingdom

2009 - SIAM Fellow For contributions to linear algebra, systems, and control and their applications in engineering.

2007 - IEEE Medal of Honor For exceptional development of powerful algorithms in the fields of communications, computing, control and signal processing.”

2006 - Jack S. Kilby Signal Processing Medal For seminal contributions to the theory and applications of statistical signal processing.

2000 - IEEE Claude E. Shannon Award

2000 - Member of the National Academy of Sciences

1994 - Fellow of the American Academy of Arts and Sciences

1991 - Fellow, The World Academy of Sciences

1984 - Member of the National Academy of Engineering For outstanding contributions in prediction, filtering, and signal processing, and for leadership in engineering.

1970 - IEEE Fellow For inspired teaching of and contributions to information, communication, and control theory

1969 - Fellow of John Simon Guggenheim Memorial Foundation

Fellow of the Indian National Academy of Engineering (INAE)


What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Algorithm
  • Algebra

Thomas Kailath mostly deals with Algorithm, Signal processing, Estimation theory, Mathematical optimization and Electronic engineering. Thomas Kailath mostly deals with Covariance matrix in his studies of Algorithm. The various areas that Thomas Kailath examines in his Signal processing study include Direction of arrival, Speech recognition, Sensor array, Signal subspace and Multipath propagation.

His work deals with themes such as Subspace topology, Artificial intelligence, Estimation of signal parameters via rotational invariance techniques, Rotational invariance and Signal, which intersect with Estimation theory. His research investigates the connection with Mathematical optimization and areas like Applied mathematics which intersect with concerns in White noise, Stochastic process, Gaussian noise, Linear system and Hilbert space. The concepts of his Electronic engineering study are interwoven with issues in Antenna array, Antenna, Waveform and Background noise.

His most cited work include:

  • Linear systems (6333 citations)
  • ESPRIT-estimation of signal parameters via rotational invariance techniques (4902 citations)
  • Detection of signals by information theoretic criteria (2862 citations)

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

Thomas Kailath spends much of his time researching Algorithm, Signal processing, Control theory, Applied mathematics and Mathematical optimization. In Algorithm, Thomas Kailath works on issues like Sensor array, which are connected to Artificial intelligence. His Signal processing research is multidisciplinary, relying on both Signal subspace and Electronic engineering.

His Control theory study focuses on Adaptive filter in particular. His Adaptive filter research is multidisciplinary, relying on both Kalman filter and Lattice. The Applied mathematics study combines topics in areas such as Stochastic process and Covariance.

He most often published in these fields:

  • Algorithm (34.34%)
  • Signal processing (15.23%)
  • Control theory (14.37%)

What were the highlights of his more recent work (between 1996-2019)?

  • Control theory (14.37%)
  • Algorithm (34.34%)
  • Applied mathematics (13.94%)

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

Thomas Kailath mainly investigates Control theory, Algorithm, Applied mathematics, Mathematical optimization and Mathematical analysis. The concepts of his Control theory study are interwoven with issues in Minimum phase, Norm, Signal reconstruction and Equalization. His work is dedicated to discovering how Minimum phase, Robustness are connected with Estimation theory and other disciplines.

His Algorithm study incorporates themes from Kalman filter and Theoretical computer science. His Applied mathematics study combines topics from a wide range of disciplines, such as Linear estimation, Finite horizon and Toeplitz matrix. His Mathematical optimization research includes elements of Stochastic process and Adaptive filter.

Between 1996 and 2019, his most popular works were:

  • Indefinite-quadratic estimation and control: a unified approach to H 2 and H ∞ theories (449 citations)
  • Iterative decoding for MIMO channels via modified sphere decoding (256 citations)
  • Multizone bake/chill thermal cycling module (249 citations)

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

  • Statistics
  • Algorithm
  • Algebra

Thomas Kailath mainly focuses on Algorithm, Control theory, Applied mathematics, Algebra and Equalization. His Algorithm research incorporates elements of Matrix, Detection theory and System of linear equations. In his research on the topic of Detection theory, Subspace topology and Artificial intelligence is strongly related with Pattern recognition.

His research in Control theory intersects with topics in Estimation theory, MIMO and Signal reconstruction. His Applied mathematics study also includes

  • Linear estimation and related Series,
  • H filter, which have a strong connection to Linear matrix inequality and Mathematical optimization. His study looks at the relationship between Transmission and fields such as Electronic engineering, as well as how they intersect with chemical problems.

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.

Top Publications

Linear systems

Thomas Kailath.

10657 Citations

ESPRIT-estimation of signal parameters via rotational invariance techniques

R. Roy;T. Kailath.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1989)

6961 Citations

Detection of signals by information theoretic criteria

M. Wax;T. Kailath.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1985)

4072 Citations

On spatial smoothing for direction-of-arrival estimation of coherent signals

Tie-Jun Shan;M. Wax;T. Kailath.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1985)

2229 Citations

The Divergence and Bhattacharyya Distance Measures in Signal Selection

T. Kailath.
IEEE Transactions on Communications (1967)

2141 Citations

Blind identification and equalization based on second-order statistics: a time domain approach

Lang Tong;Guanghan Xu;T. Kailath.
IEEE Transactions on Information Theory (1994)

1407 Citations

ESPRIT--A subspace rotation approach to estimation of parameters of cisoids in noise

R. Roy;A. Paulraj;T. Kailath.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1986)

1276 Citations

A generalized state-space for singular systems

G. Verghese;B. Levy;T. Kailath.
IEEE Transactions on Automatic Control (1981)

1258 Citations

A least-squares approach to blind channel identification

Guanghan Xu;Hui Liu;Lang Tong;T. Kailath.
IEEE Transactions on Signal Processing (1995)

1012 Citations

Fast, recursive-least-squares transversal filters for adaptive filtering

J. Cioffi;T. Kailath.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1984)

929 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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