Xu (Sunny) Wang, Wilfrid Laurier University
Associate Professor
Co-Program Director Shad Laurier, Department of Mathematics
Waterloo, Ontario
xwang@wlu.ca
Office:
(519) 884-0710 ext. 4845
Expert In
Bio/Research
I received my PhD in Statistics from the University of Waterloo in 2007 and both my M.Sc. in Statistics and B.Sc. in Applied Mathematics from Tianjin University in 1999 and 2002 respectively.
Prior to joining Laurier, I was a postdoctoral fellow in the Department of Statistics and Actuar...
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Prior to joining Laurier, I was a postdoctoral fellow in the Department of Statistics and Actuar...
Click to Expand >>
Bio/Research
I received my PhD in Statistics from the University of Waterloo in 2007 and both my M.Sc. in Statistics and B.Sc. in Applied Mathematics from Tianjin University in 1999 and 2002 respectively.
Prior to joining Laurier, I was a postdoctoral fellow in the Department of Statistics and Actuarial Science at the University of Waterloo (2007-2009), and spent seven years (2009-2016) as an tenure-track assistant professor later tenured associate professor in the Department of Mathematics, Statistics and Computer Science at St. Francis Xavier University (Nova Scotia, Canada).
My research program focuses on developing new statistical tools to analyze, model, and interpret complex systems such as human dynamics and high dimensional multimodal data arising from medical research. This research lies at the intersection of modern statistical learning and "traditional" statistical ideas.
Currently I am focusing on two research directions:
-Develop efficient statistical models and algorithms for describing, analyzing and interpreting human behaviour data, such as email communication, emergency calls etc. The ultimate goal of the first research direction is to propose a flexible model, which does not require domain knowledge and is interpretable.
-Develop automated statistical learning tools for analyzing high dimensional multimodal data. To overcome the difficulties in analyzing high dimensional multimodal data from multiple sources, we propose to develop a hybrid approach that interactively combines methods from statistics, computational topology and deep learning.
Click to Shrink <<
Prior to joining Laurier, I was a postdoctoral fellow in the Department of Statistics and Actuarial Science at the University of Waterloo (2007-2009), and spent seven years (2009-2016) as an tenure-track assistant professor later tenured associate professor in the Department of Mathematics, Statistics and Computer Science at St. Francis Xavier University (Nova Scotia, Canada).
My research program focuses on developing new statistical tools to analyze, model, and interpret complex systems such as human dynamics and high dimensional multimodal data arising from medical research. This research lies at the intersection of modern statistical learning and "traditional" statistical ideas.
Currently I am focusing on two research directions:
-Develop efficient statistical models and algorithms for describing, analyzing and interpreting human behaviour data, such as email communication, emergency calls etc. The ultimate goal of the first research direction is to propose a flexible model, which does not require domain knowledge and is interpretable.
-Develop automated statistical learning tools for analyzing high dimensional multimodal data. To overcome the difficulties in analyzing high dimensional multimodal data from multiple sources, we propose to develop a hybrid approach that interactively combines methods from statistics, computational topology and deep learning.
Click to Shrink <<