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, network epidemics, 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 to Machine Learning
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.