Welcome to the Department of Statistics and Actuarial Science

The Department of Statistics and Actuarial Science is among the top academic units for statistical and actuarial science in the world and is home to more than 40 research active full-time faculty working in diverse and exciting areas. The Department is also home to over 900 undergraduate students and about 150 graduate students in programs including Actuarial Science, Biostatistics, Quantitative Finance, Statistics, and Statistics-Computing.

We are located on University of Waterloo main campus, which is located at the heart of Canada's Technology Triangle about 100 kilometers west of Toronto.

  1. Oct. 19, 2018Undergraduate Student Research Awards (USRA)

    DEADLINE for Winter 2018 is October 19, 2018

    The Undergraduate Student Research Awards (USRA) are sponsored by the Natural Sciences and Engineering Research Council (NSERC) of Canada.  The Department of Statistics and Actuarial Science has 6 awards available for Winter 2019 term.

    This award allows you to conduct research in a university environment full time for a term. The goal is to stimulate your interest in research and to encourage students to enroll in graduate studies in Statistics and Actuarial Sciences.  If you would like to gain research work experience that complements your studies in an academic setting, this award provides you with financial support.

    Continue reading on the USRA page

  2. Sep. 20, 2018The Department of Statistics and Actuarial Science is pleased to welcome Assistant Professor Peijun Sang as of September 1, 2018

    It is with great pleasure that the Department of Statistics and Actuarial Science at the University of Waterloo welcomed Assistant Professor Peijun Sang.

    Peijun (Perry) Sang is a tenure-track assistant professor. He received his PhD in Statistics from Simon Fraser University in 2018. His research interests include functional data analysis, high dimensional regression, copula modeling and risk analysis.

  3. Sep. 20, 2018It is with great pleasure that the Department of Statistics and Actuarial Science at the University of Waterloo welcomes Professor Jeroen de Mast.

    Jeroen de Mast is a visiting full professor who will be in Waterloo every Fall term for the next number of years. He received his PhD in Industrial Statistics from the University of Amsterdam in 2002 and until recently was also a professor in the Business School at the University of Amsterdam.

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  1. Sep. 27, 2018Department seminar by Yuanying Guan, Indiana University Northwest

    Agent-based Asset Pricing, Learning, and Chaos

    The Lucas asset pricing model is one of the most studied model in financial economics in the past decade. In our research, we relax the original assumptions in Lucas model of homogeneous agents and rational expectations. We populate an artificial economy with heterogeneous and boundedly rational agents. By defining a Correct Expectations Equilibrium, agents are able to compute their policy functions and the equilibrium pricing function without perfect information about the market. A natural adaptive learning scheme is given to agents to update their predictions. We examine the convergence of equilibrium with this learning scheme and show that the equilibrium is learnable (convergent) under certain parameter combinations. We also investigate the market dynamics when agents are out of equilibrium, including the cases where prices have excess volatility and the trading volume is high. Numerical simulations show that our system exhibits rich dynamics, including a whole cascade from period doubling bifurcations to chaos.

  2. Sep. 29, 2018Waterloo Datathon - Fall 2018Datathon Logo

    We are extending an invitation to a select group of talented undergraduate, graduate and PhD students to participate in the upcoming University of Waterloo Datathon.

  3. Oct. 4, 2018Department seminar by Hongzhe Li, University of Pennsylvania

    Methods for High Dimensional Compositional Data Analysis in Microbiome Studies

    Human microbiome studies using high throughput DNA sequencing generate  compositional data with the absolute abundances of microbes not recoverable from sequence data alone. In compositional data analysis, each sample consists of proportions of various organisms with a unit sum constraint. This simple feature can lead traditional statistical methods when naively applied to produce errant results and spurious associations. In addition, microbiome sequence data sets are typically high dimensional, with the number of taxa much greater than the number of samples. These important features require further development of methods for  analysis of high dimensional compositional data.  This talk presents several latest developments in this area, including methods for estimating the compositions based on sparse count data,  two-sample test for compositional vectors and  regression analysis with compositional covariates.  Several microbiome studies at the University of Pennsylvania are used to illustrate these methods and several open questions will be discussed.

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Faculty Joint Publications

Map of Faculty and PhD Students backgrounds

Meet our people

Matthias Schonlau

Matthias Schonlau


Contact Information:
Matthias Schonlau

Matthias Schonlau's personal website

Research interests

Professor Schonlau's research interests include applied survey sampling and survey methodology, machine learning from text data such as open-ended questions as well as software implementation of his research.