Mathematical and statistical sciences, University of Alberta
Course Based Master of Science in Modeling, Data and Predictions
Are you good in Math or Stats? Are you aspiring for a data-science related career? The course based MDP program is designed to help you achieve your goals!
Admission Status
Open
Applications for Fall 2025 semester start
are now open
are now open
Applications for Fall 2025 semester start
will close January 15, 2025
Program Details
Faculty:
Science
Delivery Mode:
On Campus
Program Type:
Course Based
Program Duration:
16 months - Full time
Part time options available
Degree Level:
Master of Science
Faculty Mentors
The MDP Program is supported and managed by a team of Faculty Mentors who are top researchers in their fields and experienced in interdisciplinary and industrial research training of students. Many of their trainees have successful data-science related careers in industry and government.
Professor Christoph Frei
Email:
cfrei@ualberta.ca
Website:
www.math.ualberta.ca/~cfrei/
Office:
CAB 621
In his research, Professor Christoph Frei uses and develops mathematical and statistical tools to address important problems in finance and economics. His current research is in mathematical finance (algorithmic trading and credit risk management) and mathematical economics (over-the-counter markets and the economics of digital currencies). He has been collaborating with several financial institutions and companies.
Professor Bin Han
Email:
bhan@ualberta.ca
Website:
www.ualberta.ca/~bhan/
Office:
CAB 541
Professor Bin Han is an expert in applications of on wavelet/framelet methods, Fourier transform methods and sparse approximation and sampling methods in image processing, data sciences, deep learning algorithms, functional data analysis, and scientific computation.
Professor Bei Jiang
Email:
bei1@ualberta.ca
Website:
www.ualberta.ca/~bei1/
Office:
CAB 435
Professor Bei Jiang is a Canada CIFAR AI Chair. Her research expertise includes joint modeling of longitudinal and health outcome data, Bayesian hierarchical modeling, mixture modeling functional and imaging dta analysis, kernel machine regression/classification, and Bayesian Support Vector Machine. She has extensive experiences in collaborations with industry and government agencies. Many of her former students work at data related positions in government, public health agencies, financial institutions and AI companies.
Professor Linglong Kong
Email:
lkong@ualberta.ca
Website:
www.ualberta.ca/~lkong/
Office:
CAB 431
Professor Kong is a Canadian Research Chair in Statistical Learning, as well as a Canada CIFAR AI Chair. His research interests include statistical machine learning, high-dimensional data analysis, neuroimaging data analysis, robust statistics and quantile regression. He has been collaborating with several financial institutions and companies. Many of his former students work as at data related positions in government, public health agencies, financial institutions and AI companies.
Professor Michael Li
Email:
myli@ualberta.ca
Website:
www.ualberta.ca/~myli/
Office:
CAB 643
Professor Michael Li research field is in Applied Mathematics. His research expertise include mathematical studies of nonlinear differential equations and dynamical systems, and the mathematical modeling of infectious diseases and in public health. Many of his former students work as data scientists and analysts in public health agencies, financial institutions and data companies.
Professor Ivan Mizera
Email:
imizera@ualberta.ca
Website:
www.stat.ualberta.ca/~mizera/
Office:
CAB 411
Bio coming
Professor Jay Newby
Email:
jnewby@ualberta.ca
Website:
newby-jay.github.io/
Office:
CAB 529
Professor Newby's expertise includes applied stochastic processes, mathematical modeling, and machine learning tools for bio-image analysis. His research is mechanistic stochastic modeling of molecular motion, biomechanics, and chemistry in micron-scale environments such as cells and extracellular polymer matrices. He is involved in several collaborations with researchers in mucosal immunology and cell biology. He also co-founded the startup company AI Tracking Solutions, a cloud-based machine learning app for automated particle tracking analysis of 2D and 3D microscopy videos.
Professor Hao Wang
Email:
hao8@ualberta.ca
Website:
www.math.ualberta.ca/~hwang/
Office:
CAB 545B
Professor Hao Wang is Tier 1 Canada Research Chair in Mathematical Biosciences and Director of Interdisciplinary Lab for Mathematical Ecology & Epidemiology (ILMEE). His research field is in Mathematical Biology with focus on mathematical modeling and analysis of ecological and epidemiological systems using nonlinear differential equations and dynamical systems. Some of his former students work as data scientists and analysts in financial institutions and technology companies.
Faculty Contacts
Have questions regarding the MDP Program? We would love to hear from you and answer your questions!
PROGRAM COORDINATOR
Ms Jane Cooper
Email:
mssmdp@ualberta.ca
Phone: 1 (780) 492-3396
Fax: 1 (780) 492-6826