CANSSI Ontario Research Day
This is a free, hybrid event that welcomes attendees both online (via Zoom) and in person (at Chestnut Conference Centre, 89 Chestnut St, Toronto, ON).
The CANSSI Ontario Research Day will showcase the work and discoveries by the data sciences and statistics community in Ontario. This one-day event draws participants from many Ontario universities, public, not-for-profit, and the research sector for a full day of data and discoveries.
There is much debate among practitioners and scholars about what data science is. Join us on September 29, 2022, where you will hear some of the top experts in the field engage in informed, insightful discussions as they unravel the definitions of data science.
Registration is free.
Lunch, as well as drinks and snacks during the morning and afternoon breaks, will be provided.
Seating is available on a first come, first served basis, subject to venue capacity
September 29, 2022
- 9:45 am - 10:00 am
- Welcoming Remarks
- 10:00 am - 11:00 am
- Some Statistical Issues in Population, Clinical and Laboratory COVID-19 Research
- The COVID-19 pandemic has stimulated intensive interdisciplinary collaborations aiming to advance understanding of the population dynamics of infection, develop vaccines, and identify effective therapeutic interventions. This talk will describe three public health, clinical and laboratory research projects in COVID-19 research with an emphasis on the statistical challenges and methodology. The projects will be presented in the order they arose over the course of the pandemic. Specific topics include reporting delay adjustments to provincial and national infection rates, rapid design and cost-effective execution of a clinical trial assessing the therapeutic effect of convalescent plasma, and evaluating the vaccine response to individuals with autoimmune disease. Understanding the data acquisition and reporting processes is shown to be critically important, highlighting the need for careful planning as well as a good public health infrastructure for population research.
- 11:00 am - 11:05 am
- 11:05 am - 12:30 pm
- Presentations by Ontario-based Researchers
- Gengming He, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
Develop novel statistical methods for analyzing long-read sequencing data to investigate the genetic mechanism of cystic fibrosisDavid Li, Department of Statistical Sciences, University of Toronto.
A Poisson Cluster Process with Cluster-Dependent Marking for Detecting Ultra-Diffuse GalaxiesBoxi Lin, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
Sex-stratified vs. sex-combined analysis in the presence of genetic effect heterogeneity.YuChung Lin, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
Incorporating Functional Annotations in Polygenic Risk Scores Improves Generalizability to Cross-Ethnic PopulationsSamar Salah Mohamedahmed, Center for Addiction and Mental Health (CAMH), Pharmacogenetics Research Clinic
Genetic and Polygenic Risk Analysis of Antidepressant Response and Cognitive Domains in Late-Life DepressionAlina Selega, Lunenfeld-Tanenbaum Research Institute
Multi-objective Bayesian Optimization with Heuristic Objec- tives for Biomedical and Molecular Data Analysis WorkflowsDivya Sharma, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
Hybrid CNN-LSTM model for disease prediction using longitudinal microbial dataTeresa Tsui, Sunnybrook Research Institute
Accounting for uncertainty in health utilities to inform cancer drug funding decisionsNicholas, Waglechner, Lunenfeld-Tanenbaum Research Institute, Sinai Health in Toronto
Genomic Epidemiology of Mycobacterium abscessus in a Canadian Cystic Fibrosis CentreChangchang Xu, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
Penalized maximum likelihood inference of mixture cure model under multiple imputationJingxiong Xu, Lunenfeld-Tanenbaum Research Institute
A Novel Gene-Based Test for Sequencing Studies Based on a Bayesian Variable Selection of Rare VariantsZiang Zhang, Department of Statistical Sciences, University of Toronto.
An indirect test of gene-environment interaction for binary traitLehang Zhong, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto.
RoPE: a robust profile likelihood method for differential gene expression analysisJunhao Zhu, Department of Statistical Sciences, University of Toronto.
LLOT in Reconstruction of Spatial Expression
Speakers:Alina Selega, Boxi Lin, Changchang Xu, Dayi (David) Li, Divya Sharma, Gengming He, Jingxiong Xu, Junhao Zhu, Lehang Zhong, Samar Salah Mohamedahmed Elsheikh, Teresa Tsui, YuChung Lin, Ziang Zhang
- 1:10 - 2:00 pm
- Poster Session | Lunch
- 2:00 - 3:15 pm
- Panel Discussion: What is Data Science?
- Moderated by:
Rohan Alexander, Assistant Director, CANSSI Ontario; Assistant Professor, Faculty of information and Department of Statistical Sciences, University of Toronto
Marsha Chechik, Professor, Department of Computer Science, University of Toronto
Mark Daley, Chief Digital Officer, Professor, Department of Computer Science, University of Western Ontario
Donald Estep, Director, CANSSI; Professor, Department of Statistics and Actuarial Science, Simon Fraser University
Amber Simpson, Professor, School of Computing and Department of Biomedical and Molecular Sciences, Queen’s University
Amber Simpson Professor, School of Computing and Department of Biomedical and Molecular Sciences, Queen’s University
Donald Estep Director, CANSSI, Professor, Department of Statistics and Actuarial Science, Simon Fraser University
Mark Daley Chief Digital Officer, Professor, Department of Computer Science, University of Western Ontario
Richard Cook University Professor and Mathematics Faculty Research Chair, Department of Statistical and Actuarial Sciences, Faculty of Mathematics; University WaterlooRichard CookUniversity Professor and Mathematics Faculty Research Chair, Department of Statistical and Actuarial Sciences, Faculty of Mathematics; University Waterloo
Richard Cook is a Professor in the Department of Statistics and Actuarial Science, Faculty of Mathematics Research Chair, and University Professor at the University of Waterloo. He holds a cross-appointment in the School of Public Health (UW) and a part-time appointment in the Faculty of Health Science at McMaster University. His research interests include the analysis of life history data, the design and analysis of clinical and epidemiological studies, and statistical methods for the analysis of incomplete data. He has published extensively in these areas and written two books with Jerry Lawless. He is also deeply engaged in collaborative research with other scientists working in transfusion medicine, immunology, and cancer, and consults widely with industry and government organizations. In 2018 he was awarded the Gold Medal of the Statistical Society of Canada and in 2021 he was named a Fellow of the Royal Society of Canada.
Rohan Alexander Assistant Director, CANSSI Ontario Assistant Professor, Faculty of information and Department of Statistical Sciences University of Toronto