Science Menu
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.
| Name | Department | Research Interest |
|---|---|---|
| James Gu | Architectural and Engineering Technology | Reliability and probability analysis, numerical modeling of engineering systems, disaster resilient built environments, etc. |
| Jonathan Van Hamme | Biological Sciences | Environmental microbiology, biodegradation, bioremediation, pollutants, microbiology, biocatalyst |
| Matthew Reudink | Biology | Ornithology, animal ecology, evolution of plumage in birds, animal behaviour |
| Stan Miles | Bob Gaglardi School of Business and Economics | Computational Economics, Computational Finance, Genetic Programming |
| Nelaine Mora-Diez | Chemistry | Computational chemistry: thermodynamic and kinetic studies of organic systems of environmental, biochemical, or chemical importance; Applications of machine learning methods; Calculation of equilibrium constants in the gas phase and in solution; Kinetic studies in the gas phase and in solution; calculation of reaction mechanisms; Atmospheric chemistry; Excited states and photochemistry. |
| Ajay Dhruv | Computing Science | Statistical machine learning, deep learning, hyperparameter tuning and optimization, generative AI, fine-tuning large language models, recommender systems, computer vision |
| Md Moniruzzaman | Computing Science | Reinforcement machine learning, Computer vision, Quantum machine learning, Blockchain, Quantum-safe systems, Artificial intelligence-driven blockchain cybersecurity, Peer-to-peer Marketplace, Energy informatics, Precision agriculture |
| Mila Kwiatkowska | Computing Science | Medical decision support systems, database systems and data mining, biomedical informatics |
| 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 |
| Nisha Puthiyedth | Computing Science | Bioinformatics, machine learning, computational biology, comparative genomics, big data anaylsis |
| Piper Jackson | Computing Science | Data science, computational social science, simulation, transdisciplinary research, programming languages, formal methods, gerontology, software development |
| Yan Song | Computing Science | Image classification and segmentation, vision-based object detection and tracking, human activity recognition and detection; machine learning models and deep neural networks; semi-supervised and weakly supervised learning |
| Muhammad Hanif | Engineering | Wireless communications, 5G and beyond communications, internet of things, machine learning, signal processing |
| Munima Jahan | Engineering | Machine Learning for Software Engineering, Large Language Models, Automated Model Generation from Requirements, Requirements Verification, Natural Language Processing, Gender Disparity in Engineering Education |
| Sina Keshvadi | Engineering | Network Measurement, Internet Architecture, Internet Security |
| Yasin Mamatjan | Engineering | Software engineering for healthcare and biomedical research; translational research in bioinformatics and biomedical engineering; big data and machine learning for cancer genomics |
| Zeinab Teimoori | Engineering | Applied AI, ML, Quantum AI, Generative AI, Sustainable Transportation, Smart Cities, Electric Vehicles, Blockchain |
| David Hill | Geography | Data mining and modeling methods, complex environmental systems problems, fate and transport of contaminants, decision trees, artificial neural networks, etc. |
| 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 |
| Salman Kimiagari | Management, Info and Supply Chain | International Business and Quantitative Marketing, International Marketing, International Entrepreneurship, Market Engineering and Operation Research |
| Erfanul Hoque | Mathematics and Statistics | Longitudinal data analysis; Statistical learning/Machine learning; Spatial statistics; Generalized (General) linear Mixed models; Measurement errors; Missing data analysis; Biostatistics; Statistical computing; Time series analysis; and Dynamic data science with applications in transportation, electricity demand, supply chain, algorithmic trading, option pricing and medical research. |
| Jabed Tomal | Mathematics and Statistics | Statistical machine learning, big data, Bayesian statistical inference and statistical ecology |
| 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 |
| 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 |
| Rick Brewster | Mathematics and Statistics | Discrete mathematics, theoretical Computing Science, computational complexity, graph theory, polynomial time algorithms and good characterizations |
| Roger Yu | Mathematics and Statistics | Graph theory, discrete optimization, data analysis, network optimization, operations research |
| Sean Hellingman | Mathematics and Statistics | Statistical modelling, sports analytics, multi-level models, statistical learning, stochastic modelling for sports tracking data, survival analysis |
| Yana Nec | Mathematics and Statistics | Applied analysis, modelling and optimization, numerical and graphical simulation, applications in natural sciences and engineering |
| Yue Zhang | Mathematics and Statistics | Bioinformatics, Comparative genomics, Applied statistics, Big data analysis, Statistical inference, Mathematical and statistical methods for evolutionary biology and genetics |
| John Church | Natural Resource Science | Sustainability of cattle industry, range management, meat production, beef production |
| Anila Virani | Nursing | Use of health informatics in chronic disease management such as diabetes, stroke and dementia, and technology-enabled learning |
| Michael Flannigan | Predictive Services, Emergency Management and Fire Science | Fire weather, climate change, fire behaviour, fire growth modelling, fire management, machine learning |
| 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 |
| 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 |
