Queen's University
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Graduate Studies

School of

Graduate Studies

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Mathematical Engineering


"The graduate mathematics community at Queen's is vibrant, international, and intellectually stimulating. The faculty and students are a tight-knit group, with research and career guidance from internationally recognized faculty members always at one's fingertips. My graduate education in the mathematics department prepared me superbly the next steps in my career in applied mathematics and engineering, and I couldn't recommend it more highly."

John Treilhard, M.Sc., 2014

Program Contact

Jennifer Read
Graduate Assistant
Department of Mathematics & Statistics
Queen's University
Kingston, ON, Canada K7L 3N6

Phone: 613.533.2405
E-mail: gradapp@mast.queensu.ca
Website: www.mast.queensu.ca


Program Overview

Our graduate programs in Mathematics and Engineering area ideally suited for students interested in a mathematical perspective on engineering.  Research in mathematics and engineering takes place in the broad areas of communication and information theory, control theory, signal processing and various fields of applied mathematics.  Graduate students in Mathematics and Engineering come from a variety of backgrounds:  mathematics; applied mathematics, electrical engineering; mechanical engineering.

See "Why Grad Studies" videos by Queen's Engineering faculty and students


The Department has strong collaborative ties between its Mathematics and Engineering faculty and members of other departments within the Faculty of Engineering and Applied Science, especially in the areas of communications and control theory.  

Career paths – employment opportunities

Graduates from the Mathematics and Engineering programs have gone on to rewarding careers in industry, finance and academia.

Degrees Offered/Method of Completion

Degrees Offered

M.A.Sc.: 18-24 months

Ph.D.: 4 years

Method of Completion

M.A.Sc.: Course work and a research thesis

Ph.D.: Course work, comprehensive exam and research thesis

Fields of study and Supervisors

Research in Mathematics and Engineering and Applied Mathematics takes place in the broad areas of communication and information theory, control theory, signal processing and various fields in applied mathematics. Applicants are encouraged to review the research interests of our faculty members.

Selim Akl - akl@cs.queensu.ca
Design and Analysis of Algorithms, Parallel Computing, Biomedical Computing, Unconventional Computation

Fady Alajaji - fady@mast.queensu.ca
Information and communication theory, data compression, joint source-channel coding, error control codes

Gunnar Blohm - gunnar.blohm@queensu.ca
Artificial neural networks, Neuronal spike coding, Clifford algebra (dual quaternions), Bayesian statistics, Systems identification and control theory, Large-scale spiking neuronal models, Sensory-motor neuroscience

Steven Blostein - steven.blostein@queensu.ca
Signal processing for communications, wireless communications, detection and estimation theory

Bahman Gharesifard - bahman@mast.queensu.ca
Systems and control, nonlinear and geometric control, distributed control and optimization, game theory

Mark Green - greenm@civil.queensu.ca
Bridge-vehicle dynamics, repair of structures with fibre reinforced polymer (FRP) materials, prestressing applications of FRP materials, fire resistance of structures, smart and adaptive materials for structures, control of structural vibrations

Martin Guay - martin.guay@chee.queensu.ca
Control theory, Process Control, Applied Statistics

Andrew Lewis - andrew@mast.queensu.ca
Geometric control theory, diferential geometry, geometric functional analysis

Tamas Linder - linder@mast.queensu.ca
Communications, source/channel coding, data compression,  information theory; statistical pattern recognition

Abdol-Reza Mansouri - mansouri@mast.queensu.ca
Sub-Riemannian geometry, geometric control theory, stochastic analysis and Malliavin calculus

Jim McLellan - james.mclellan@queensu.ca
Nonlinear control, modelling of nonlinear chemical processes, measures of nonlinearity

Glen Takahara - takahara@mast.queensu.ca
Communication theory, communication networks, queueing theory

David Thomson - djt@mast.queensu.ca
Solar oscillations and space physics, cellular phone systems, signal processing, special functions

Serdar Yuksel  - yuksel@mast.queensu.ca
Stochastic and decentralized control, information theory,  applied probability

Funding, Academic Prerequisites & Deadline

Funding Information

M.Sc. & M.A.Sc.: Up to $23,000 a year

Ph.D.: $25,000 minimum per year

The funding package can consist of  teaching assistantships or fellowships, research assistantships, internal and external awards and/or scholarships.  We encourage all eligible students to apply for external scholarships such as NSERC or OGS.  Entering graduate students who are awarded federal government tri-council awards automatically receive a top-up of $5000 (MSc)/$10000 (Phd) from Queen’s in the first year of their program.

International students are normally awarded additional funding to help offset the higher tuition fee they must pay.

Academic Prerequisites

Master’s programs: 4 year Bachelor’s degree (normally engineering) with a minimum B+ standing and a strong interest in mathematics and statistics.

Doctoral program: In addition to the above a Master’s degree with a minimum B+ standing, demonstrated research potential and clear interests.

Application Requirements

In addition to providing all applicable information requested on the online application form, applicants must also provide two official transcripts for all postsecondary studies, at least two letters of reference and a copy of their curriculum vita.

Test Requirements

Those applicants whose native languages do not include English may be required to obtain a satisfactory standing in an English Language Proficiency Test as part of the application process.

Key Dates and Deadlines

Application Deadline: There is no deadline to apply for admission, but applicants are advised to submit their applications as soon as possible and by January 15th in order to receive full funding consideration.

Learning Outcomes

Degree Level Expectations - MASc (89 KB)

Degree Level Expectations - PhD (87 KB)