Research in the Department of Mathematics and Statistics occurs in a number of disciplines.

Pure Mathematics

Murray R. Bremner

(Emeritus) Nonassociative algebras, Representation theory, Symbolic computation

John Martin

Topology: Fixed point sets, Knot theory, theory of retracts

Steven Rayan

Algebraic geometry, Topology, Representation theory, Moduli Spaces, Mathematical physics, Integrable systems, Quantum matter, Quantum Information

Ebrahim Samei

Harmonic Analysis, Banach Algebras and Operator Spaces

E. D. Tymchatyn

(Emeritus) Topology: continuum theory

J.C. (Jiun-Chau) Wang

Functional Analysis:  non-commutative probability

Alex Weekes Representation theory, Algebraic geometry, Commutative and non-commutative algebra, Poisson and symplectic geometry, mathematical physics.
Curtis Wendlandt Representation theory, Quantum groups, Quantum symmetric pairs, Noncommutative algebra, Infinite-dimensional Lie algebras

Applied Mathematics

Alexey F. Shevyakov

Mathematical Modelling, Non linear PDE Models, Symmetry methods, Symbolic and Numerical Scientific Computation.

George Patrick

Classical mechanics, Hamiltonian systems with symmetry, structure preserving numerical simulation, mathematical physics

Artur Sowa

Mathematical physics, Mathematical modeling

Jacek Szmigielski

Integrable systems, mathematical physics

Discrete Mathematics

Gary Au
Discrete Optimization, Combinatorics, and Mathematics Education
Chris Soteros

Statistical physics, applied combinatorics, Monte Carlo simulation

Statistics

Miķelis G. Bickis

(Emeritus) Probability and Statistics

Shahedul Khan

Modeling changepoint data, Longitudinal data analysis, Bayesian inference and Markov Chain Monte Carlo, Survival Analysis

William H. Laverty

Applied statistical methods

Longhai Li

Bayesian Classification & Regression, Monte Carlo Methods, Machine Learning, Bioinformatics

Juxin Liu

Interation models, errors-in-variable models, missing data analysis, Markov chain Monte Carlo (MCMC) methodolgy

Chris Soteros

Statistical physics, applied combinatorics, Monte Carlo simulation

Raj Srinivasan

Queuing networks and Applied Probability Models

Li Xing

Analysis of Big Omics Data, Bioinformatics, Machine Learning, Bayesian Methods, Longitudinal Data Problem, and Biostatistics