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
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.
CAB 621
www.math.ualberta.ca/~cfrei/
cfrei@ualberta.ca
Professor Bin Han
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.
CAB 541
www.ualberta.ca/~bhan/
bhan@ualberta.ca
Professor Bei Jiang
Professor Bei Jiang's research experties include joint modeling of longitudinal and health outcome data, Bayesian hierarchical modeling, mixture modeling
functional and imaging data 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 as at data related positions in government, public health agencies, financial institutions and AI companies.
CAB 435
www.ualberta.ca/~bei1/
bei1@ualberta.ca
Professor Linglong Kong
Professor Kong is a Canadian Research Chair in Statistical Learning. 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.
CAB 431
www.ualberta.ca/~lkong/
lkong@ualberta.ca
Professor Michael Li
Professor Michael Li's 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.
CAB 632
www.ualberta.ca/~myli
myli@ualberta.ca
Professor Jay Newby
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.
CAB 431
newby-jay.github.io/
jnewby@ualberta.ca
Professor Hao Wang
Professor Hao Wang is a 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.
CAB 545B
www.math.ualberta.ca/~hwang/
hao8@ualberta.ca
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Professor Ivan Mizera