معرفی
Dr. Pratheepa Jeganathan is an Assistant Professor in the Department of Mathematics and Statistics at McMaster University. Her research focuses on developing statistical methods for multi-view learning, particularly in modeling dependencies across heterogeneous data sources. Applications span molecular microbiology, spatial omics, sensor-based traffic data, and loss reserving. Her methodological work includes generative models, Bayesian sampling, constrained clustering, and spatio-temporal statistics.
- Education: PhD in Mathematics (Statistics) from Texas Tech University (2016), Postdoctoral Fellowship at Stanford University (2016–2020).
- Research Interests: Spatial statistics, statistical learning, high-throughput data methods, and statistical theory.
Recent work includes analyzing microbiome interventions using transfer functions, studying vaginal microbiota communities, and applying recurrent neural networks to multivariate loss reserving. She has published in journals like PLoS Computational Biology and Genome Biology.
- Teaching: Instructs courses in data science (STATS 3DA3, CSE 780), statistical research projects, and graduate-level topics in statistics.
