The following faculty members participate in this program:

Jahrul Alam - Adaptive wavelets in atmospheric turbulence, large eddy simulation. (PhD McMaster)

Alex Bihlo - Deep learning, neural networks, Monte Carlo methods, numerical differential equations, geometric numerical integration, geophysical fluid mechanics, meteorology. (PhD Vienna)

Edward Brown - Data visualization, data privacy. (PhD Toronto)

Sharene Bungay - Genetic algorithms, mathematical modelling, numerical methods, optimization techniques, physiological systems, computational chemistry, dynamical systems. (PhD Guelph)

Candemir Cigsar - Time-to-event and event history, recurrent events, multistate modelling, sample design, biostatistics, system reliability, statistical genetics, incomplete data and goodness-of-fit. (PhD Waterloo)

Joerg Evermann - Business process analytics, process mining, process discovery, process prediction, sequence alignment, reinforcement learning. (PhD University of British Columbia)

Zhaozhi Fan - Heavy tailed distributions, measurement error, longitudinal categorical data, high frequency and high dimensional data, free probability, quantile regression, financial time series. (PhD Göttingen)

Armin Hatefi - Classification, clustering, complex data and mixture models, non-parametric and semi-parametric models, machine learning, computational statistics, big data, Bayesian statistics. (PhD Manitoba)

Ronald Haynes - Numerical analysis and scientific computing for partial differential equations (moving mesh, domain decomposition, and parallel methods in time) and linear algebra, optimization. (PhD Simon Fraser)

Matthew Hamilton - Development and application of artificial intelligence in medical image analysis, computer vision and data visualization and analytics.  Development of future video representations and codecs for XR/AR/VR and holographic displays. High-performance computing. (PhD University of Alberta).

J. Concepcion Loredo-Osti - Time series, extreme values, statistical genetics, genomics, Monte Carlo methods, dimension reduction, regression trees, neural networks, applied stochastic processes, inference. (PhD Dalhousie)

Scott MacLachlan - Numerical analysis and scientific computing, high-performance computing, numerical linear algebra, multigrid, finite-element and parallel-in-time methods, fluid dynamics. (PhD Colorado at Boulder)

George Miminis - Scientific computing, numerical methods in control engineering, numerical methods for vector, and parallel architectures. (PhD McGill)

Alwell Oyet - Longitudinal data analysis, analysis of multinomial data, spatial data analysis, statistical computing, time series analysis, and wavelets in statistics. (PhD Alberta)

Lourdes Pena-Castillo - Development and/or application of artificial intelligence or machine learning in biomedical sciences, games, augmented virtually, and methods to solve biological problems. (PhD Otto-von-Guericke University Magdeburg)

Karteek Popuri - Medical Image Analysis, Machine Learning, Deep Learning, Computational Anatomy and Big Data Epidemiological studies (PhD University of Alberta)

Vinicius Prado da Fonseca - Robotics, Tactile sensing, Robotic manipulation, Human-machine interaction, Human-robot interaction, Applied machine learning and Artificial intelligence (PhD University of Ottawa)

 Alex Shestopaloff - Computational statistics, Bayesian inference, network science, applications of statistics to finance. (PhD University of Toronto)

Amilcar Soares - Development of techniques and or applications of artificial intelligence or machine learning for spatiotemporal data enrichment, segmentation, classification, clustering, and visualization (PhD Federal University of Pernambuco, Brazil)

Terrence Tricco - Computational astrophysics, computational fluid dynamics, scientific computing, high-performance computing, numerical analysis, data visualization, data science, and synthetic data generation. (PhD Monash University) 

Hamid Usefi - Machine learning, feature selection, dimensionality reduction and various applications especially in genomics. Also interested in applications of deep learning in anomaly detection. (PhD Western Ontario)

Asokan Variyath - Computational statistics, machine learning, longitudinal data, variable selection, design of experiments, multivariate ordinal data. (PhD Waterloo)

Hong Wang - Markov processes, multi-parameter stochastic processes, martingales, order statistics, extreme values and related limiting distributions, model building, machine and deep learning. (PhD Regina)

Deping Ye - Asymptotic functional analysis, random matrices, compressed sensing, statistical models with measurement error, convex geometry, geometric analysis, quantum information theory. (PhD Case Western Reserve)

Yildiz Yilmaz-Cigsar - Survival and event history analysis, statistical genetics, genetic epidemiology, incomplete data analysis, sampling designs, multivariate analysis, copula theory, causal inference. (PhD Waterloo)

Dr. Nan Zheng: Nonlinear mixed-effects models, spatiotemporal modeling, model selection for nonlinear mixed-effects models, parametric and semi-parametric longitudinal data analysis, hidden Markov models, measurement error, likelihood and pseudo-likelihood methods for complex sampling schemes. (PhD Memorial University)