Contact Information:
Christiane Lemieux
Research interests
My main research area is quasi-Monte Carlo methods, which can be seen as a deterministic version of the Monte Carlo method for multidimensional integration and simulation. I am interested both in constructions of low-discrepancy point sets that can be used for quasi-Monte Carlo methods, and in applications of these methods within a variety of computational problems. Some of my more recent interests have been in using dependence concepts to characterize the low-discrepancy of point sets used for quasi-Monte Carlo methods; construction paradigms based on machine learning and, separately, on digital base expansions using irrational numbers such as the golden ratio, and; leveraging the use of quasi-Monte Carlo methods within machine learning algorithms to improve their efficiency.
Education/biography
I have a bachelor degree in Actuarial Science from Université Laval (1994), a Master’s degree in mathematics (1996) and a PhD in computer science (2000) from Université de Montréal. In July 2000, I joined the Department of Mathematics and Statistics at the University of Calgary as an assistant professor, where I also held a joint appointment with the Department of Computer Science. I joined the Department of Statistics and Actuarial Science in Waterloo as an associate professor in July 2006 and was promoted to full professor in July 2017. I have held many administrative roles at the University of Waterloo such as interim department chair, associate dean of graduate studies, and associate dean operations & academic.
Selected publications
Please see my UW Scholar webpage or my Google Scholar page.