# Communications and Information Theory Group

### Description of Activities

Research is conducted in the areas of information theory, communication theory, stochastic networked control systems, multi-user communication networks, data compression, error-control coding, joint source-channel coding, team decision and game theory, applied probability, Bayesian methods, statistical pattern recognition, machine learning, time-series analysis and signal processing.

Faculty | Research Interests |
---|---|

Fady Alajaji | Information and communication theory, source-channel coding, data compression, digital communications, applied probability |

Tamás Linder | Information and communication theory, source-channel coding, vector quantization, statistical pattern recognition and machine learning |

Glen Takahara | Communication networks, queuing systems, Bayesian methodology |

David J. Thomson | Statistical communications, signal processing, time series and spectrum estimation, global warming, space physics |

Serdar Yüksel | Stochastic control, networked control, information theory, source coding, probability theory and applications |

Affiliated Faculty | Primary Affiliation | Research Interests |
---|---|---|

Steven D. Blostein | Dept. of Electrical and Computer Engineering, Queen's University | Wireless communications; smart antennas; signal processing; multi-user communications |

Navin Kashyap | Adjunct Professor, Dept. of Electrical and Computer Engineering, Indian Institute of Science | Discrete applied mathematics; coding for data communication and storage; source coding; data synchronization; information theory; symbolic dynamics |

Postdoctoral Fellows

Graduate Students

Undergarduate Projects

Publications Archive

Courses Offered:

Math 800 - Seminar

Math 806 - Introduction to Coding Theory

Math 834 - Optimization Theory and Applications

Math 872 - Control of Stochastic Systems

Math 874 - Information Theory

Math 877 - Data Compression and Source Coding

Stat 855 - Stochastic Processes and Applications

Stat 864 - Discrete Time Series Analysis

Application for Graduate Studies:

Queen's provides an ideal environment to do graduate study in
Mathematics and
Engineering, Applied Mathematics or Mathematics or Statistics. Our
course curriculum is rigorous and increasingly diverse. The applicants
should follow the guidelines listed here.
Typically students with backgrounds in mathematics, applied
mathematics, electrical and computer engineering and systems
engineering with strong interests in
mathematical sciences will find the graduate program very stimulating
and rewarding.

Our research environment is enhanced by a very active group of graduate students. There is always a steady stream of visiting scholars and post-doctoral fellows.