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.
News
Cecilia Cotton and Jordan Hamilton win Distinguished Teacher Awards
Congratulations to Cecilia Cotton and Jordan Hamilton, recipients of the 2024 Distinguished Teacher Awards from Waterloo’s Centre for Teaching Excellence. Since 1975, the award has been given annually to four exemplary instructors from across the university who have a “record of excellent teaching over an extended period at Waterloo, usually at least five years.”
Read the full article on the Faculty of Mathematics website.
Qiuqi Wang Won the 2024 SSC Pierre Robillard Award
The Statistical Society of Canada (SSC) citation reads: "The Pierre Robillard Award is awarded annually by the SSC to recognize the best Ph.D. thesis in probability or statistics defended at a Canadian university during the previous year.
Qiuqi Wang is the 2024 winner of the Pierre Robillard Award of the Statistical Society of Canada. Qiuqi’s thesis, entitled "Characterizing, optimizing and backtesting metrics of risk", was written while he was a doctoral student at the University of Waterloo working under the supervision of Ruodu Wang."
Read the full article on the SSC website.
Ruodu Wang and Aukosh Jagannath named Canada Research Chairs
Two professors from the Faculty of Mathematics have been named NSERC Canada Research Chairs. Ruodu Wang, professor of actuarial science and quantitative finance, has been named a Tier 1 NSERC CRC in Quantitative Risk Management, and Aukosh Jagannath, assistant professor of statistics and actuarial science, has been named a Tier 2 NSERC CRC in Mathematical Foundations of Data Science.
Events
Life History Analysis and Survey Sampling Methodology – A Conference Celebrating the 80th Birthdays of Jerry Lawless and Mary Thompson
The Department of Statistics and Actuarial Science is delighted to announce that it is hosting a conference to celebrate the remarkable contributions of Jerry Lawless and Mary Thompson to the fields of life history analysis and survey sampling methodology. An exciting program of speakers has been lined up for what promising to be a stimulating and enjoyable two days of talks by leading researchers including collaborators, friends and former students of Mary and Jerry.
A banquet will be held on the evening of the 28th.
Organizing Committee
Richard Cook (Chair)
Joel Dubin
Pengfei Li
Peijun Sang
Changbao Wu
Yeying Zhu
Email sasevent@uwaterloo.ca for any general event inquiries.
Master of Actuarial Science (MActSc) 15th Anniversary Event
The Master of Actuarial Science (MActSc) program is celebrating its 15th anniversary. Join us at Federation Hall on Friday, May 31st, for a cocktail reception and dinner. Everyone is welcome!
Early bird tickets: $55 per person (rate available until April 19th)
Regular ticket: $65 per person
David Sprott Distinguished Lecture by Bhramar Mukherjee
Distinguished Lecture Series
Bhramar Mukherjee
John D Kalbfleisch Distinguished University Professor of Biostatistics
Siobán D. Harlow Collegiate Professor of Public Health
Chair of the Department of Biostatistics
University of Michigan
Room: DC 1302
The Data Struggle of the Unseen
Despite several proposed roadmaps to increase diversity in scientific research, most of the world's research data are collected on people of European ancestry. We rely on summary statistics from historically privileged populations and then devise clever statistical methods to transfer/transport them for cross-ancestry use. In this talk, I would first argue the obvious: for building fair algorithms we need fair training datasets. However, till we have reached the dream of equitable big data at a global scale, statisticians have an important role to play. In fact we have the perfect tools to study the "unobserved" through modeling of missing data, selection bias and alike. I will share examples from my personal journey as a statistician where doing good and timely statistical work with imperfect data quantified important disparity in health outcomes and led to policy impact. I will conclude the talk with a call to arms for statisticians to lead efforts for creating, curating, collecting data and pioneering new scientific studies, not just remain on the design and analytic fringes. As public health statisticians, our job is not just to predict, but to prevent. The talk is based on years of work with my students and colleagues at the Department of Biostatistics, University of Michigan and inspired by the transformative experience we shared as a statistical team working on the COVID-19 pandemic.