2025

• Large Scale Change Detection Using Remote Sensing Data
  • Annual Meeting of the Statistical Society of Canada, Saskatoon SK
  • Slides
• The Role and Impact of Statistics in Industry, Public Policy, and Public Health Initiatives (panel discussion)
  • Annual Meeting of the Statistical Society of Canada, Saskatoon SK

2024

• AI and Landscape Management (panel discussion)
  • Ontario Professional Forestry Association Conference, Sault Ste. Marie ON

2023

• A Novel Approach to Stratification in the Foothills of the Sierra Nevada Mountains Using Automated Landscape Segmentation and Remote Sensed Imagery and LiDAR Data
  • Society of American Foresters National Convention, Sacramento CA

2022

• Generalized Soft Impute for Matrix Completion
  • ICSA-Canada Chapter 2022 Symposium, Banff AB
• Generalized Soft Impute for Matrix Completion
  • University of Calgary Statistics Seminar, Calgary AB
  • Slides
• Generalized Soft Impute for Matrix Completion
  • Annual Meeting of the Statistical Society of Canada, Online
  • Winner of the Award for Best Presentation by a New Investigator
  • Slides
• What kind of training do students  in Statistics and Data Science need? (panel discussion)
  • Inaugural CANSSI-Prairies Summit, Winnipeg MB

2021

• Investigating text data using Topological Data Analysis

  • Annual Meeting of the Statistical Society of Canada, Online

• Analyser les tweets de chefs politiques canadiens grâce à l’Analyse Topologique de Données

  • UQAM Statistics Seminar, Université du Québec à Montréal, Montréal QC
  • Slides

• Investigating text data using Topological Data Analysis

  • Machine Learning Special Interest Group, University of Manitoba, Winnipeg MB
  • Slides

2020

• Arbitrary-precision linear algebra in R using RcppEigen and BH

  • useR 2020, Online conference
  • Slides and Video

• How to see in 100 dimensions: Transforming your data to better understand it

  • Science Public Online Talks, University of Manitoba, Winnipeg MB
  • Slides and Video

• Principal Component of Explained Variance: High-Dimensional Estimation and Inference

  • Statistics Seminar, University of Winnipeg, Winnipeg MB
  • Slides

2019

• Principal Component of Explained Variance: High-Dimensional Estimation and Inference

  • PhD Thesis Defense, McGill University, Montreal QC
  • Slides

• A Tracy-Widom Empirical Estimator For Valid P-values With High-Dimensional Datasets

  • ICSA-Canada Chapter 2019 Symposium, Queen’s University, Kingston, ON
  • Slides
  • Demo

• casebase: An alternative framework for survival analysis

  • Bioinformatics-Biostatistics Research Seminar, University of Manitoba, Winnipeg MB
  • Slides
  • Package website

2018

• Principal Component of Explained Variance: High-Dimensional Estimation and Inference

  • Joint Special Seminar, Departments of Statistics and Computer Science, University of Manitoba, Winnipeg MB
  • Slides

• Nonlinear Dimension Reduction to Improve Predictive Accuracy in Genomic and Neuroimaging Studies

  • Annual Meeting of the Statistical Society of Canada, Montreal QC
  • Abstract
  • Slides

2017

• Reduced-Rank Singular Value Decomposition for Dimension Reduction with High-Dimensional Data

  • Annual Meeting of the Statistical Society of Canada, Winnipeg MB
  • Winner of the 2017 Student Research Presentation Award
  • Abstract
  • Slides

• A Novel Approach To Competing-Risk Analysis Using Case-Base Sampling

  • Fifth Annual Canadian Statistics Student Conference, Winnipeg MB
  • Slides

2016

• Principal Component of Explained Variance: An Efficient and Optimal Data Dimension Reduction Framework for Association Studies

  • Annual Meeting of the Statistical Society of Canada, St. Catherines ON
  • Abstract
  • Slides

• A novel approach to competing risks analysis using case-base sampling

  • Research Day, Department of Epidemiology, Biostatistics and Occupational Health, McGill University
  • Winner of the Dr. Jim Hanley Research Day Award for Best Presentation in Biostatistics
  • Slides

2015

• Principal Component of Explained Variance: An Efficient and Optimal Data Dimension Reduction Framework for Association Studies

  • Montreal Genomics Monthly Meeting
  • Slides

• Efficient dimension-reduction technique for the joint analysis of correlated phenotypes

  • Annual Human and Statistical Genetics Meeting, Vancouver BC
  • Slides