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 community is engaged in topics such as actuarial science, biostatistics, data science, quantitative finance, statistics, & statistics-computing. Our department is home to more than 60 full-time faculty researching diverse and exciting areas, over 1000 undergraduate students from around the world, and more than 175 graduate students in master, doctoral, and professional programs. 

Undergraduate programs Graduate Programs
  1. Mar. 16, 2023Math Teach-Off turns teaching and learning into friendly competition
    Nathaniel Stevens teaching at a whiteboard

    On March 1, 2023, faculty and undergraduate students from the Faculty of Mathematics participated in what they hope will be merely the first “Math Teach-Off” event.

    The premise of the event was simple: three groups of students would take a quiz on the mathematical concept. Then, each group would be taught about the concept for an hour by one of three instructors: Nathaniel Stevens (assistant professor of Statistics and Actuarial Science and Director of the undergraduate Data Science program); Jordan Hamilton (lecturer in the Math Undergraduate Group); and Blake Madill (lecturer in Pure Mathematics). Finally, the students would take a second quiz on the concept, and each group’s scores would be compared for improvement and overall accuracy.

    Continue reading on the Faculty of Math's website.

  2. Feb. 9, 2023Professor Nathaniel Stevens recipient of the 2023 ASQ Feigenbaum Medal
    Nathaniel Stevens

    The Department of Statistics and Actuarial Science congratulates professor Nathaniel Stevens as being named the winner of the 2023 ASQ Feigenbaum Medal. This achievement is awarded for the "outstanding characteristics of leadership, professionalism, and potential in the field of quality and also whose work has been or, will become of distinct benefit to mankind." (ASQ)

    The citation reads: "For outstanding contributions to the development and application of statistics in business and industry, to the mentoring of undergraduate and graduate students, and to the service of the broad Quality community."

    The medal will be presented in Philadelphia at 2023 ASQ's World Conference on Quality and Improvement

  3. Feb. 6, 2023Professor Stefan Steiner recipient of the 2023 ASQ Shewhart Medal
    Stefan Steiner

    The Department of Statistics and Actuarial Science congratulates professor Stefan Steiner as being named the winner of the 2023 ASQ Shewhart Medal. This achievement is awarded for the "outstanding technical contributions and leadership in the field of modern quality control and improvement, especially through the development of theory, principles, techniques, and successful applications in the area of quality." (ASQ)

    The citation reads: "For his outstanding leadership in the field of industrial statistics; for his innovation and technical contributions in measurement system analysis, process monitoring, statistical engineering, and variation reduction; and for his dedicated promotion of quality improvement in business, industry, and healthcare."

    The medal will be presented in Philadelphia at 2023 ASQ's World Conference on Quality and Improvement

Read all news
  1. Mar. 24, 2023Seminar by Hao Xing

    Please Note: This seminar will be given in person.

    Actuarial Science and Financial Mathematics seminar series 

    Hao Xing
    Boston University

    Room: M3 3127

    The Dark Side of Circuit Breakers

  2. Mar. 27, 2023Seminar by Kateryna Tatarko

    Please Note: This seminar will be given in person.

    Probability seminar series 

    Kateryna Tatarko
    University of Waterloo

    Room: M3 3127

    Randomized Petty projection inequality

  3. Mar. 28, 2023Seminar by Zelalem Negeri

    Please Note: This seminar will be held in-person.

    Student seminar series

    Zelalem Negeri
    Assistant Professor, University of Waterloo

    Location: M3 3127

    Latent class models for an individual participant data meta-analyses of diagnostic test accuracy studies

All upcoming events

Meet our people

Changbao Wu

Changbao Wu

Professor / Chair

Contact Information:
Changbao Wu

Changbao Wu's personal website

Research interests

Professor Wu has a primary research interest in the design and analysis of complex surveys. His research also covers more broad topics including semiparametric and nonparametric methods, resampling (jackknife and bootstrap) techniques, missing data and measurement error problems. He has worked extensively on empirical likelihood (EL) methods and related computational procedures, with strong interest in developing R packages for practical implementations of the EL methods.