معرفی
Justin Slater is an Assistant Professor in the Department of Math and Stats at the University of Guelph, starting in January 2023. His research focuses on Bayesian methods in statistical epidemiology, including infectious disease modeling, spatio-temporal analytics, and evidence synthesis. He holds a PhD from the University of Toronto (2023), an MSc from Queen’s University (2016), and a BSc from Dalhousie University (2014).
Education:
- PhD in Statistical Sciences, University of Toronto (2019–2023)
- MSc in Statistics, Queen’s University (2016)
- BSc (Honours) in Math and Statistics, Dalhousie University (2014)
Research Themes:
- Infectious Disease Statistics: Developing statistical models for epidemic prediction and uncertainty quantification.
- Spatio-Temporal Analytics: Leveraging cellphone mobility data for infectious disease modeling across disciplines like agriculture and veterinary sciences.
- Bayesian Statistics: Prior elicitation, hierarchical models in sparse data contexts, and Bayesian mixture models.
- Evidence Synthesis: Improving meta-analytic and adaptive trial methods for combining randomized and observational studies.
Awards:
- NSERC Postgraduate Scholarship – Doctoral (PGS-D), 2021
His work bridges statistical theory and real-world applications, particularly in public health decision-making. No grants or lab affiliations are explicitly detailed in the provided text.
۰مقاله منتشرشده
