Department of Mathematics and Statistics

Department of Mathematics and Statistics
Department of Mathematics and Statistics

Communications and Information Theory

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.

Full-Time 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 theory, stochastic dynamical systems, networked control, information theory, source coding and quantization

 

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

 

Graduate 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 on our Application Information page. 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.