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.

Contact Info

Department of Math & Stats
Jeffery Hall, University Ave.
Kingston, ON Canada, K7L 3N6
Phone: (613) 533-2390
Fax: (613) 533-2964