TRU Science

Supervisors

The faculty members listed below are eligible to supervise graduate students in the Master of Science in Data Science. They may be contacted directly to discuss potential opportunities for studying under their supervision.

Note:  Only students choosing the thesis option require a supervisor prior to their application to the program.


NameDepartmentResearch Interest
Rick Brewster Mathematics and Statistics Discrete mathematics, theoretical Computing Scienceence, computational complexity, graph theory, polynomial time algorithms and good characterizations
John Church Natural Resource Science Sustainability of cattle industry, range management, meat production, beef production
Haytham El Miligi Computing Science Mobile application development; multi-core real-time system; 3d network-on-chips modeling and optimization
Avninder Gill Management, Info and Supply Chain Business analytics, fuzzy Logics, optimization and meta-heuristics (genetic algorithms and simulated annealing) in supply chain, operations and other business areas
Claudia Gonzalez Psychology Using physiological data including brain activity, eye tracking, body kinematics and other physiological measures, to investigate human behavior and the links with brain function across human populations
James Gu Architectural and Engineering Technology Reliability and probability analysis, numerical modeling of engineering systems, disaster resilient built environments, etc.
David Hill Geography Data mining and modeling methods, complex environmental systems problems, fate and transport of contaminants, decision trees, artificial neural networks, etc.
Piper Jackson Computing Science Data science, computational social science, simulation, transdisciplinary research, programming languages, formal methods, gerontology, software development
Mila Kwiatkowska Computing Science Medical decision support systems, database systems and data mining, biomedical informatics
Becky Lin Mathematics and Statistics Likelihood inference, computational statistics, statistical machine learning or neural network modeling for big data with a focus on acoustic data, and data visualization
Yana Nec Mathematics and Statistics Applied analysis, modelling and optimization, numerical and graphical simulation, applications in natural sciences and engineering
Catherine Ortner Psychology Multi-level modelling to analyze mouse-tracking, eye-tracking, daily diaries, and mobile application data, to assess cognitive process underlying emotion regulation choices and predictors of emotion regulation
Andrew Park Computing Science Using various AI techniques including machine learning to analyze and visualize big data such as crime data, court data, Dark web forum data, etc.
Musfiq Rahman Computing Science Research in wireless technologies such as Near Field Communication (NFC), Internet of Things (IoT), smartphone applications, Radio Frequency Identification (RFID), use machine learning and big data analysis to predict forest fire
Matthew Reudink Biology Ornithology, animal ecology, evolution of plumage in birds, animal behaviour
Mateen Shaikh Mathematics and Statistics Computational statistics, clustering, classification, statistical learning, machine learning, data mining, association rules, pattern recognition, visualization, longitudinal data, biostatistics, microarray analysis, next-generation sequencing analysis
Xiaoping Shi Mathematics and Statistics Graph-based change-point detection for high-dimensional data, variable selection and asymptotic analysis, composite likelihood inference, image denoising, bioequivalence studies
Mohamed Tawhid Mathematics and Statistics Metaheuristic algorithms, inspired computing, computational intelligence, evolutionary computation, artificial intelligence and their applications to data analysis, Big Data, Operations Research, computational optimization, simulations, modelling, scientific computation
Jabed Tomal Mathematics and Statistics Statistical machine learning, big data, Bayesian statistical inference and statistical ecology
Jonathan Van Hamme Biological Sciences Environmental microbiology, biodegradation, bioremediation, pollutants, microbiology, biocatalyst
Yan Yan Computing Science Bioinformatics, Machine Learning, Complex Network and Big Data Analysis
Roger Yu Mathematics and Statistics Graph theory, discrete optimization, data analysis, network optimization, operations research