CANSSI Ontario Research Day 2024
This is a free, in-person event.
Overview
The CANSSI Ontario Research Day will showcase the work and discoveries by early-career researchers in the 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.
2024 Themes
Financial, Actuarial, and Data Sciences, Big Data, Health Data, and Statistics Theory.
Registration
- 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.
- If you are a PhD student interested in presenting at the poster session, please register here
Poster
Hourly Schedule
May 22, 2024
- 9:30 am - 10:00 am
- Light Breakfast
- 10:00 am - 10:05 am
- Welcoming Remarks
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Speakers:
Lisa Strug
- 10:05 am - 11:25 am
- Presentations by Ontario-based Researchers
Devan Becker, Department of Mathematics, Wilfrid Laurier University
Identification of Variants of Concern Without Knowing What a Variant isXin Bing, Department of Statistical Sciences, University of Toronto
Linear Discriminant Regularized RegressionSanjeena Dang, School of Mathematics and Statistics, Carleton University
A parsimonious family of mixtures of multivariate Poisson log-normal factor analyzers for clustering count dataUtkarsh Dang, School of Mathematics and Statistics, Department of Health Sciences, Carleton University
Modeling data from rare diseases: a spotlight on Duchenne muscular dystrophy-
Speakers:
Devan Becker, Sanjeena Dang, Utkarsh Dang, Xin Bing
- 11:25 am - 11:30 am
- Break
- 11:30 am - 12:30 pm
- Presentations by Ontario-based Researchers
Osvaldo Espin Garcia, Department of Epidemiology and Biostatistics, University of Western Ontario
Finding your niche: Launching a research program in biostatisticsKevin Granville, Department of Mathematics and Statistics, University of Windsor
Investigating changes in the timing of Ontario's wildland fire season: a spatial perspectivePratheepa Jeganathan, Department of Mathematics and Statistics, McMaster University
Enhancing LDA for Longitudinal Microbiome Studies-
Speakers:
Brian Ling, Kevin Granville, Osvaldo Espin Garcia, Pratheepa Jeganathan
- 12:30 pm - 1:10 pm
- Lunch & Trainee Poster Session
- 1:10 pm - 3:10 pm
- Presentations by Ontario-based Researchers
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Brian Ling, Department of Mathematics and Statistics, Queen's University
Nonparametric Likelihood Ratio Test for Univariate Shape-constrained DensitiesPouria Ramazi, Faculty of Mathematics & Statistics, Brock University
The shortcut-PC algorithmKelly Ramsay, Department of Mathematics and Statistics, York University
Differentially private projection-depth-based mediansJustin Slater, Department of Mathematics & Statistics, University of Guelph
Overdispersed or under-reported? A practical look at network autoregressions for under-reported infectious disease dataLan Wen, Department of Statistics and Actuarial Science, University of Waterloo
Estimating the average causal effects of food substitution strategiesJoseph Jay Williams, Computer Science, University of Toronto
TBD
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Speakers:
Joseph Jay Williams, Justin Slater, Kelly Ramsay, Lan Wen, Pouria Ramazi
- 3:10 pm - 3:15 pm
- Closing Remarks
- 3:15 pm - 3:30 pm
- Transition to 2024 DLSS with Dr. Susan Holmes
- Register here: https://canssiontario.utoronto.ca/event/2024-dlss-susan-holmes/
Location
Speakers
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Brian LingAssistant Professor, Department of Mathematics and Statistics, Queen's University
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Kevin Granville
Assistant Professor, Department of Mathematics and Statistics, University of Windsor
Kevin GranvilleAssistant Professor, Department of Mathematics and Statistics, University of Windsor
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Osvaldo Espin GarciaAssistant Professor, Epidemiology and Biostatistics, University of Western Ontario
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Pratheepa JeganathanAssistant Professor, Department of Mathematics and Statistics, McMaster University
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Sanjeena DangAssociate Professor & CRC in Data Science & Analytics, School of Mathematics and Statistics, Carleton University
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Xin BingAssistant Professor, Department of Statistical Sciences, University of Toronto
