معرفی
Peter MacDonald is an Assistant Professor at the University of Waterloo, specializing in statistical methodology, network analysis, and medical informatics. His research focuses on developing statistical techniques for complex data structures, including network data and electronic health records. He also works on hypothesis testing methodologies and false discovery rate control in high-dimensional settings.
Key research areas include predictive modeling for oncological outcomes, latent variable models for multiplex networks, and adaptive testing procedures for grouped hypotheses. His work bridges theoretical statistics with applied problems in healthcare and biomedical research.
Notable contributions include machine learning approaches for predicting esophageal adenocarcinoma using EHR data and advancements in network analysis through latent space models. His articles frequently address methodological challenges in modern statistical inference, particularly in handling structured and high-dimensional data.
No specific academic awards or grants are listed in the provided information. His current affiliations include the University of Waterloo faculty, though specific department/school details are not explicitly stated in the text.
