معرفی
Ryan Browne is an Assistant Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds a BMath (2004), MMath (2006), and PhD (2009) from the same institution. His research focuses on model-based clustering, classification, and measurement system quality assessment, with applications in multivariate analysis and statistical inference. He is particularly known for contributions to mixture models and their computational optimization.
- Education:
- BMath in Statistics, University of Waterloo (2004)
- MMath in Statistics, University of Waterloo (2006)
- PhD in Statistics, University of Waterloo (2009)
Ryan’s work emphasizes flexible statistical methodologies, including advancements in skewed distributions, high-dimensional data analysis, and robust algorithms for clustering and classification. He has received the prestigious 2011 W.J. Youden Award from the American Statistical Association for his PhD research on measurement system evaluation.
His research trends span computational statistics (e.g., sketching algorithms for big data) and model-based clustering innovations (e.g., mixtures of generalized hyperbolic distributions). Recent work explores parsimonious models, nested Gaussian structures, and efficient parameter estimation for complex datasets.
- Key Awards:
- 2011 W.J. Youden Award (American Statistical Association)
Ryan collaborates on applied projects, including industrial ecology and sensory data analysis. He has developed R packages like mixture and MixGHD, which implement his methodological contributions.
