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Home>profiles>maxturgeon

Max Turgeon

Profile
Select Publications
Max Turgeon
Dimension reduction; High-dimensional data; Statistical genetics
Assistant Professor
(204) 220-1169
Max.Turgeon@umanitoba.ca

Research and Teaching Interests

My main research interests are dimension reduction methods for high-dimensional data. This includes linear approaches (e.g. PCA, CCA, PCEV, PLS) as well as nonlinear approaches (e.g. manifold learning, autoencoders). High-dimensional data is challenging to analyse because of the so-called “curse of dimensionality”. However, we can mitigate this curse by using the structure in the data to our advantage.

I am interested in developing statistical methodologies that are statistically and computationally efficient. I am also interested in applications to statistical genetics, genomics, and neuroimaging.

Courses taught

  • Fall 2019: STAT 4690—Applied Multivariate Analysis (course website)
  • Winter 2020: STAT 7200—Multivariate Statistics (course website)
  • Fall 2020: STAT 3150—Statistical Computing
  • Winter 2021: SCI 2000—Introduction to Data Science (course website)

Links

https://www.maxturgeon.ca/

Turgeon, M., Oualkacha, K., Ciampi, A., Miftah, H., Dehghan, G., Zanke, B.W., Benedet, A.L., Rosa-Neto, P., Greenwood, C.M.T., Labbe, A., for the Alzheimer’s Disease Neuroimaging Initiative. “Principal component of explained variance: an efficient and optimal data dimension reduction framework for association studies”. Statistical Methods in Medical Research, 27: 2018. doi:10.1177/0962280216660128.

Wang, Y., Murphy, O., Turgeon, M., Wang, Z.Y., Bhatnagar, S.R., Schulz, J., and Moodie, E.E.M. “The perils of quasi-likelihood information criteria”, Stat, 4: 2015. doi:10.1002/sta4.95

Ahmad, O.S., Morris, J.A., Mujammami, M., Forgetta, V., Leong, A., Li, R., Turgeon, M., Greenwood, C.M.T., Thanassoulis, G., Meigs, J.B., Sladek, R., and Richards, J.B. “A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease” Nature Communications, 6: 2015. doi:10.1038/ncomms8060

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