Welcome to 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 70 full-time faculty researching diverse and exciting areas, over 2000 undergraduate students from around the world, and approximately 200 graduate students in master, doctoral, and professional programs.
News
Changbao Wu, 2026 Statistical Society of Canada Gold Medalist
Changbao Wu, Professor in the Department of Statistics and Actuarial Science at the University of Waterloo, is the recipient of the 2026 Gold Medal of the Statistical Society of Canada (SSC), the Society’s highest honour.
New Book by Ali Ghodsi Explores Foundations and Advances in Deep Learning
Ali Ghodsi, professor in the Department of Statistics and Actuarial Science, has co-authored a new textbook, Elements of Deep Learning.
The book offers a comprehensive introduction to deep learning and neural networks, combining mathematical rigor with hands-on practice. Covering both foundational concepts and emerging topics, the text explores areas including convolutional neural networks, Transformers, large language models, diffusion models, graph neural networks, reinforcement learning, and more.
Professor Ruodu Wang honoured with 2026 Frontiers of Science Award
Ruodu Wang, Canada Research Chair in Quantitative Risk Management and professor in the Department of Statistics and Actuarial Science, has received the 2026 Frontiers of Science Award (FSA) from the International Congress of Basic Sciences (ICBS), shared with his co-author Vladimir Vovk, professor at Royal Holloway, University of London, for the paper titled “E-values: Calibration, combination, and applications” published in the Annals of Statistics in 2021. (See the paper on arXiv or view the journal website.)
Events
Statistics seminar: Yanjun Han
Yanjun Han
New York University
Room: M3 3127