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

Interested in graduate studies with Statistics and Actuarial Science? Meet Mingyu (Bruce) Feng, a PhD student in actuarial science. Bruce is a pioneer researcher in the field of sustainable investment and the impact of climate change. Learn more about furthering your education on the Future Graduate page on the Math site.

  1. Oct. 28, 2021Sprott Scholarship Announcement

    The Sprott Scholarship is named after Professor D.A. Sprott, the founding Chair of the Department of Statistics and Actuarial Science, and is awarded annually to a registered full-time student who has been recognized by the Department as having shown particular promise in research in the PhD program prior to the final approval of their thesis. The selection is made by the Awards subcommittee of the Statistics and Actuarial Science Graduate Committee.

    Congratulations to the 2020 recipients:

  2. Oct. 12, 2021Stefan Steiner awarded the 2021 Don Owen Award from the American Statistical Association's San Antonio Chapter
    Stefan Steiner
     

    The American Statistical Association's San Antonio Chapter recently distinguished Stefan Steiner with the 2021 Don Owen Award. The award was presented at the 2021 Conference of Texas Statisticians, held virtually on October 9 and hosted by Texas Tech University.

    The accolade is given annually to a statistician who embodies the three-fold accomplishments of Dr. Donald B. Owen. Owen excelled in the areas of research, statistical consultation, and service to the statistical community.

  3. Oct. 8, 2021Christiane Lemieux Appointed Associate Dean Operations and Academic of the Faculty of Mathematics
    Christiane Lemieux
    Professor Christiane Lemieux of the Department of Statistics and Actuarial Science is appointed Associate Dean Operations and Academic of the Faculty of Mathematics, starting January 1, 2022, for a 3-year term.
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  1. Dec. 2, 2021Department seminar by Eardi Lila

    Please Note: This seminar will be given online.

    Statistics & Biostatistics seminar series

    Eardi Lila
    University of Washington

    Link to join seminar: Hosted on Zoom

    Functional random effects modeling of complex brain data

  2. Dec. 6, 2021Department seminar by Lisa Gao

    Please Note: This seminar will be given online.

    Department seminar

    Lisa Gao
    University of Wisconsin-Madison

    Link to join seminar: Hosted on Zoom

    A Marked Spatial Point Process for Insurance Claims Management

  3. Dec. 8, 2021Department seminar by Olya Mandelshtam

    Please Note: This seminar will be given online.

    Probability seminar series

    Olya Mandelshtam
    University of Waterloo

    Link to join seminar: Hosted on Zoom

    TBA

All upcoming events

Meet our people

Mu Zhu

Mu Zhu

Professor / Director – Data Science Program, Graduate

Contact Information:
Mu Zhu

Mu Zhu personal website

Research interests

Mu's initial research interest was dimension reduction. In the early years of his faculty career, he devoted much attention to efficient kernel machines for rare target detection and ensemble methods for variable selection. He also worked on algorithms for making personalized recommendations, and applications of machine learning to healthcare informatics.

While ensemble learning continued to captivate his curiosity, in more recent years Mu explored a hodgepodge of different topics—such as evaluation metrics, protein structures, transactional networks, and genetic epistasis. At present, he is studying various problems about dependence modeling, large covariance matrices, and generative neural networks.