TRU Science

Supervisors

The faculty members listed below are eligible to supervise (full) or co-supervise (associate) graduate students in the Master of Science program in Data Science. They may be contacted directly to discuss potential opportunities for studying under their supervision.


Name Department Status as supervisor in MSc Data Science Research Interest
Lingling Jin Computing Science Full Data-driven modelling, prediction and simulation of genome evolution in plants, encompassing formal language theory, computational modelling, machine learning
Haytham El Miligi Computing Science Full Mobile application development; multi-core real-time system; 3d network-on-chips modeling and optimization
Mohamed Tawhid Mathematics and Statistics Full 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
Roger Yu Mathematics and Statistics Full Graph theory, discrete optimization, data analysis, network optimization, operations research
Xiaoping Shi Mathematics and Statistics Full Graph-based change-point detection for high-dimensional data, variable selection and asymptotic analysis, composite likelihood inference, image denoising, bioequivalence studies
Mila Kwiatkowska Computing Science Full Medical decision support systems, database systems and data mining, biomedical informatics
Jabed Tomal Mathematics and Statistics Full Statistical machine learning, big data, Bayesian statistical inference and statistical ecology
Andrew Park Computing Science Full Using various AI techniques including machine learning to analyze and visualize big data such as crime data, court data, Dark web forum data, etc.
Mateen Shaikh Mathematics and Statistics Full Computational statistics, clustering, classification, statistical learning, machine learning, data mining, association rules, pattern recognition, visualization, longitudinal data, biostatistics, microarray analysis, next-generation sequencing analysis
David Hill Geography Full Data mining and modeling methods, complex environmental systems problems, fate and transport of contaminants, decision trees, artificial neural networks, etc.
James Gu Architectural and Engineering Technology Full Reliability and probability analysis, numerical modeling of engineering systems, disaster resilient built environments, etc.
Catherine Ortner Psychology Full 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
Piper Jackson Computing Science Full Data science, computational social science, simulation, transdisciplinary research, programming languages, formal methods, gerontology, software development
Avninder Gill Management, Info and Supply Chain Full Business analytics, fuzzy Logics, optimization and meta-heuristics (genetic algorithms and simulated annealing) in supply chain, operations and other business areas
Yana Nec Mathematics and Statistics Full Applied analysis, modelling and optimization, numerical and graphical simulation, applications in natural sciences and engineering
Matthew Reudink Biology Full Ornithology, animal ecology, evolution of plumage in birds, animal behaviour
Rick Brewster Mathematics and Statistics Full Discrete mathematics, theoretical Computing Scienceence, computational complexity, graph theory, polynomial time algorithms and good characterizations
Musfiq Rahman Computing Science Full 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
John Church Natural Resource Science Full Sustainability of cattle industry, range management, meat production, beef production
Claudia Gonzalez Psychology Associate 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