Welcome to the Department of Statistics and Actuarial Science

The Department of Statistics and Actuarial Science is a top tier academic unit among statistical and actuarial science globally. Our students and faculty explore topics such as Actuarial Science, Biostatistics, Data Science, Quantitative Finance, Statistics, & Statistics-Computing. Our department is home to:

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full-time faculty researching diverse and exciting areas

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undergraduate students from around the world

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 graduate students in Master, Doctoral, and professional programs

Upcomming David Sprott Distinguished Lecture by Hans Föllmer on September 26.    Distinguished Lecture Banner

Upcomming Distinguished Lecture by Paul Glasserman on October 11.       Paul Glasserman

New Conference: Waterloo Student Conference in Statistics, Actuarial Science and FinanceGraduate student conference  Registration SpeakersScheduleAccommodations

  1. Sep. 20, 2019Celebrating Mary Thompson's 50th anniversary in the Department of Statistics and Actuarial Science
    (From the left) Jerry Lawless, Jock Mackay, Mary Thompson, Winston Cherry, Steve Brown, Bovas Abraham, and Jack Robinson.

    On Wednesday, September 18, 2019, the Department of Statistics and Actuarial Science (SAS) celebrated the 50th anniversary of Professor Mary Thompson as a faculty member in the department. Many current faculty and staff and a number of retired professors gathered in the SAS Lounge and celebrated Mary’s milestone with cake, coffee and fruits. The Vice-President, Research & International, of University of Waterloo, Professor Charmaine Dean, who was a PhD graduate from the department, sent a beautiful bouquet to congratulate Mary on this special occasion. A couple retired faculty members turned the clock back and told stories about Mary during the early days of the department. Mary thanked the department for being her academic home for the past 50 years, and told the younger generation of faculty members that SAS is a “can-do” place to fulfill their full potential and aspiration.  

    Mary joined the department in 1969 as one of the first group of statistics faculty members, when the department was still in its infancy (established in 1967). Over the past half a century, Mary has become a fixture of the department, a highly accomplished scholar, and a great inspiration and role model for many students and young faculty members. She has provided dedicated services to the statistical community at all levels, including chair of the department, acting dean of the faculty, first scientific director of the Canadian Statistical Sciences Institute, and president of the Statistical Society of Canada.

  2. Sep. 16, 2019Phelim Boyle named Fellow of the Royal Society of Canada
    Phelim Boyle

    The Department of Statistics and Actuarial Science would like to congratulate Phelim Boyle, along with two other Faculty of Mathematics researchers, on being named a fellow of the Royal Society of Canada (RSC). They are among the seven University of Waterloo researchers to receive this honour and among 93 new fellows elected by their peers for outstanding scholarly, scientific, and artistic achievement across Canada.

    Phelim is a professor emeritus at Waterloo and a professor of business and economics and Wilfrid Laurier University. He is an actuary whose seminal research work in finance and insurance has won international recognition. He uses mathematical models to solve problems at the interface of these fields. Boyle has made pioneering contributions to quantitative finance and his ideas have transformed how actuaries handle financial risk. His research has influenced financial practice by providing sophisticated tools for financial institutions to better manage their risks.

    Read the full article on Math News.

  3. Sep. 4, 2019Graduate studies: a consistent model for success
    Students working on a blackboard

    Four graduate students were awarded a departmental research presentation award by the Department of Statistics and Actuarial Science, but that's not all they have in common. They all came to Waterloo because they knew of the excellence of the Statistics programs, research, and professors. Their backgrounds vary, as do their research areas, but they have all had a great experience.

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  1. Sep. 26, 2019David Sprott Distinguished Lecture by Hans Föllmer, Humboldt University Berlin

    Optimal Transport, Entropy, and Risk Measures on Wiener space


    We discuss the interplay between entropy, large deviations, and optimal couplings on Wiener space.

    In particular we prove a new rescaled version of Talagrand’s transport inequality. As an application, we consider rescaled versions of the entropic risk measure which are sensitive to risks in the fine structure of Brownian paths. 

  2. Oct. 3, 2019Department seminar by Hulin Wu, University of Texas

    Real World EHR Big Data: Challenges and Opportunities


    The real world EHR and health care Big Data may bring a revolutionary thinking on how to evaluate therapeutic treatments and clinical pathways in a real world setting. Big EHR data may also allow us to identify specific patient populations for a specific treatment so that the concept of personalized treatment can be implemented and deployed directly on the EHR system. However, it is quite challenging to use the real world data in treatment assessment and disease predictions due to various reasons. In this talk, I will share our experiences on EHR and health care Big Data research. First, I will discuss the basic infrastructure and multi-disciplinary team that is necessary in order to deal with the EHR data. Then I will use an example of  subarachnoid hemorrhage (SAH) study to demonstrate a procedure with eight steps that we have developed to use EHR data for research purpose. In particular, the EHR data extraction, cleaning, pre-processing and preparation are the major steps that require more novel statistical methods to deal with. Finally I will discuss the challenges and opportunities for statisticians to use EHR data for research.

  3. Oct. 10, 2019Department seminar by Jiaguo Cao, Simon Fraser University 

    Finding Common Modules in a Time-Varying Network


    Finding functional modules in gene regulation networks is an important task in systems biology. Many methods have been proposed for finding communities in static networks; however, the application of such methods is limited due to the dynamic nature of gene regulation networks. We propose a statistical framework for detecting common modules in the Drosophila melanogaster time-varying gene regulation network. We then develop both a significance test and a robustness test for the identified modular structure. We apply an enrichment analysis to our community findings, which reveals interesting results. Moreover, we investigate the consistency property of our proposed method under a time-varying stochastic block model framework with a temporal correlation structure. Although we focus on gene regulation networks in our work, our method is general and can be applied to other time-varying networks.

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