$30 – $125
Inaugural CANSSI Prairies Summit

Inaugural CANSSI Prairies Summit

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$30 – $125

Event Information



University of Manitoba

66 Chancellor's Circle

Winnipeg, MB R3T 2N2


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Event description
Join us in person or online for the inaugural CANSSI Prairies Summit to celebrate the launch of the CANSSI Prairies Regional Centre.

About this event

This event marks the launch of the Canadian Statistical Sciences Institute's fourth regional centre, CANSSI Prairies (covering Manitoba, Saskatchewan, Northwest Territories and Nunavut).

Day 1 of the Summit consists of an afternoon workshop and a virtual student poster session. Day 2 features a full day of activities, including a keynote address, two panel discussions, invited talks, and an in-person student poster session.

There are several registration options:

Register for Day 1 Workshop

  • Student Rate – $30
  • Regular Rate – $50

Register for Two-day Ticket

  • Student Rate – $70
  • Regular Rate – $125

Student Poster Competition: All undergraduate and graduate student at universities in Manitoba and Saskatchewan are eligible to enter a Student Poster Competition that offers cash awards as well as participation in a virtual or in-person poster session during the Prairies Summit.

Find out how to enter the Student Poster Competition

Summit Schedule

Day 1 | Tuesday, May 24

Inaugural CANSSI Prairies Summit image

1–4 p.m. CDT | Workshop

Statistical Language Modelling with R

Dr. Dave Campbell, Carleton University & Bank of Canada

Senate Chamber, E3-262 EITC, Fort Garry Campus, University of Manitoba | Attend in person or on Zoom

Workshop Description

Analysis of numeric and categorical data has unlocked incredible insights over the past century. However, tools for these data types are not amenable to the contents of legal documents, news briefings, emails, product descriptions, or social media posts. Text data requires a different set of tools to extract descriptive insights and test hypotheses. This workshop will use R and Tidyverse tools to showcase statistical language modelling tools through hands-on tutorials outlining common use cases. Extensions and more complex modelling approaches will be outlined along with their costs, risks, and potentially more meaningful insights. The first half of the workshop will focus on sentiment analysis; producing descriptive statistics and performing hypothesis tests. The second half will focus on clustering documents. Bring a computer with RStudio (version >2021.09.0) and R (version >4.1) installed and be prepared to run the analysis live during the workshop. Code and datasets will be provided for the hands-on workshop.

Prerequisite: Familiarity with Base R and/or Tidyverse

About Dr. Dave Campbell

Dr. Dave Campbell is computational statistics methodologist with a penchant for collaboration and a strong interest in ensuring student employability. He is a full Professor in the School of Mathematics and Statistics and the School of Computer Science at Carleton University and also the Assistant Director of Data Science Applications at the Bank of Canada.

Before moving to Ottawa in 2019, Dave was an Associate Professor at Simon Fraser University in the Department of Statistics and Actuarial Science, where he led the creation of their BSc in Data Science. He was the inaugural President of the Data Science and Analytics Section of the Statistical Society of Canada and a co-organizer of the Vancouver Learn Data Science Meetup (>5000 members).

Dr. Campbell researches inferential algorithms at the intersections of statistics with machine learning, computing, and applied mathematics to solve problems in forensic science, environmental toxicology, paleo-climatology, psychology, economics, and more. He has co-authored discussion papers in Bayesian Analysis and the Journal of the Royal Statistical Society (series B) and been awarded over $3.5 million in research grants. His recent projects include identifying orcas from underwater acoustic hydrophones and predicting when they will cross into shipping lanes (funded by the Department of Fisheries and Oceans), improving uncertainty quantification methods for nuclear magnetic resonance (funded by the National Research Council of Canada), and developing inferential statistical language processing tools for quantifying covariate effects in language. At Carleton he supervises a team of grad students and post-doctoral fellows. At the Bank of Canada he is often hiring new recruits with strong computing and statistics skills. Find him on LinkedIn.

4–5 p.m. CDT | Virtual Student Poster Session

Research Innovations in Statistics and Data Science

Day 2 | Wednesday, May 25

NOTE: All Day 2 in-person activities will take place in the Basic Medical Sciences Building, Theatre-A (Frederic Gaspard Room), Bannatyne Campus, University of Manitoba, unless otherwise indicated

8–9 a.m. CDT | Breakfast

9–10 a.m. CDT | Welcome and Opening Talks (Concurrent)

  • Welcome message
  • Dr. Donald Estep, Director, CANSSI
  • Dr. Brian Mark, Dean, Faculty of Science, University of Manitoba
  • Dr. Liqun Wang, Head, Department of Statistics, University of Manitoba
  • Dr. Lisa Lix, Professor and Associate Head, Department of Community Health Sciences & Director, Data Science Platform, George & Fay Yee Centre for Healthcare Innovation, University of Manitoba
  • Additional speakers to be announced
Inaugural CANSSI Prairies Summit image

10–11 a.m. CDT | Keynote Address

Data Science, Statistics and Health, with a Focus on Statistical Learning and Sparsity

Dr. Robert Tibshirani, Stanford University

Basic Medical Sciences Building, Theatre-A (Frederic Gaspard Room), Bannatyne Campus, University of Manitoba | Attend in person or on Zoom

Keynote Description

First I will discuss some general issues in the application of statistics to biomedicine. These include the importance of transparency, reproducibility and simplicity. Then I will cover some recent advances in sparse modelling (lasso), including SNPnet for GWAS studies, and LassoNet, a marriage of neural nets with the lasso. This latter method does direct feature selection within the Neural Network optimization, delivering a regularization path similar to that from glmnet for the lasso.

About Dr. Robert Tibshirani

Dr. Robert Tibshirani is a Professor of Biomedical Data Science, and of Statistics, at Stanford University. He has made important contributions to the statistical analysis of complex datasets. Some of his most well-known contributions are the Lasso, which uses L1 penalization in regression and related problems, generalized additive models and Significance Analysis of Microarrays (SAM). He also co-authored five widely used books: Generalized Additive Models, An Introduction to the Bootstrap, The Elements of Statistical Learning, An Introduction to Statistical Learning, and Sparsity in Statistics: The Lasso and Its Generalizations.

Dr. Tibshirani received the COPSS Presidents' Award in 1996. Given jointly by the world's leading statistical societies, the award recognizes outstanding contributions to statistics by a statistician under the age of 40. He was elected a Fellow of the Royal Society of Canada in 2001, the National Academy of Sciences in 2012, and the Royal Society of Britain in 2019. This year he received the ISI Founders of Statistics Prize for his 1996 paper “Regression Shrinkage and Selection via the Lasso.”

11–11:30 a.m. CDT | Coffee Break

11:30 a.m.–12:30 p.m. CDT | Panel Discussion

The Role of CANSSI Prairies in Diversifying Statistics and Data Science

  • Moderator: Dr. Lisa Lix, University of Manitoba
  • Dr. Jennifer Bodnarchuk, Senior Data Scientist, Data and Applications Division, Innovation and Technology Department, City of Winnipeg
  • Ms. Parisa Azimaee, Data Scientist II, Advanced Analytics, The Wawanesa Mutual Insurance Company
  • Ms. Kristine Kroeker, Data Manager, Synthesis Health
  • Mr. Justin Dyck, Public Health Officer, Epidemiologist I, Canadian Public Health Service, Public Health Agency of Canada

12:30–1:30 pm. CDT | Lunchtime

1:30–2:30 p.m. CDT | Students and Postdocs Panel Discussion

What Kinds of Training Do Students in Statistics and Data Science Need?

  • Moderator: Dr. Robert Tibshirani, Stanford University
  • Dr. Max Turgeon, Assistant Professor of Statistics, Department of Statistics, University of Manitoba
  • Mr. Olawale Ayilara, PhD student, Department of Community Health Sciences, University of Manitoba
  • Dr. Gyanendra Pokharel, Assistant Professor of Statistics, Department of Mathematics and Statistics, University of Winnipeg
  • Mrs. Tingxuan Wu, PhD student, Department of Mathematics and Statistics, University of Saskatchewan

2:30–3:30 p.m. CDT | Overview Talk

How and Why Quantitative Psychologists Collaborate with Health/Behavioural Scientists

Dr. Sunmee Kim, Department of Psychology, University of Manitoba

Presentation Description

Quantitative psychologists contribute to the growth in knowledge regarding the theory and quantitative methods in psychological and behavioural research. One of the approaches to improve this aspect is to explore novel methods and ideas about how statistical thinking and techniques can be used to solve data-analytic and methodological challenges in substantive areas. In this talk, I will introduce two recent successful cross-disciplinary collaborations, with (1) social psychologists and (2) nutritional scientists, and illustrate why collaborations between scientists with different backgrounds, if handled effectively, are a powerful tool for innovative research and highly rewarding.

About Dr. Sunmee Kim

Dr. Sunmee Kim is an Assistant Professor in the Department of Psychology at the University of Manitoba.

3:30–3:45 p.m. CDT | Closing Remarks

4–5:30 p.m. CDT | Reception

Reception will include a cash bar.


1–5:30 p.m. CDT | In-Person Student Poster Session

Research Innovations in Statistics and Data Science

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University of Manitoba

66 Chancellor's Circle

Winnipeg, MB R3T 2N2


View Map

Refund policy

Contact the organizer to request a refund.

Eventbrite's fee is nonrefundable.

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