CANSSI Ontario
CANSSI Ontario's goal is to strengthen and enhance research and training in statistical science by developing programs that promote interdisciplinary researchers and enable multidisciplinary collaborations.
CANSSI Ontario provides both province-wide leadership in the development of these programs, and local leadership for data-intensive research within the University of Toronto (U of T) community.
Nancy Reid - "Models and Likelihood"
Nancy Reid - "Lies, Damned Lies, and Statistics"
Li Hsu: Advancing Cancer Risk Prediction Across Diverse Populations: Polygenic Risk Scores & Beyond
Larissa Stanberry: Clinical Prediction Models - Signal or Noise? A Case of Heart Failure
Genevieve Wojcik: An Epidemiological Lens to Modeling Ancestry and Environment for Genetic Risk
Amy Braverman: Uncertainty Quantification for Remote Sensing Data
Ivor Cribben: The State of Play of Reproducibility in Statistics: An Update
Emily Hector: Distributed Model Building and Recursive Integration for Modeling Big Spatial Data
Dr. Marie-Pier Côté: A Fair Price to Pay: Exploiting Causal Graphs for Fairness in Insurance
Dr. Jeffrey Rosenthal: Speeding Up Metropolis Using Theorems
Dr. Josée Dupuis: Exploiting Family History Information to Detect Rare Variant Associations
George Davey Smith: Mendelian Randomization - what it was, what it is, and what it should become
Xinwei Deng: New Songs for Old Stories: Interface between Experimental Design and Machine Learning
Dr. Lisa Strug: Genome Data Science: Towards understanding GWAS loci
Dr. Michael Mina: Driving Public Health Systems & Fighting Pandemics with Biology, Technology & Math
Susan Holmes - Statistics and Geometry for Heterogeneous Data
Susan Holmes - Hidden Variables: Using Statistics To Decode Heterogeneous Microbiome Data
2024 CANSSI Ontario Research Day - Session 3
2024 CANSSI Ontario Research Day - Session 2
2024 CANSSI Ontario Research Day - Session 1
Dr. Michael Wu - Statistics for Keeping your Microbiome Analyses out of the Toilet
Eric Joel Tchetgen Tchetgen - "Single Proxy Control" (lecture)
Eric Joel Tchetgen Tchetgen - "Causal Inference, Semiparametric Statistics and Machine Learning"
David Keyes - "No Designer Needed: How to Create Beautiful Reports Using Only R"
William Marshall - "PyPhi: A toolbox for integrated information theory"
Sherry Zhang - "Switching between space and time: Spatio-temporal analysis with cubble"
Michael Jongho Moon - "mverse: The R package is designed to help students explore the multiverse"
Matthew Watson - "cytosel: Interactive cytometry panel design using single-cell RNA-seq"
Silvia Canelón - "Thinking Big with Maps in R: Wrangling Large Vector Data into Interactive Maps"
Osvaldo Espin-Garcia - "Converting R code into C++, Is it worth it?"