My research program seeks to understand the underlying physiology of diseases common in horses, and how these diseases can be modified with targeted nutrition, with a focus on cartilage biology.
Statistical natural language processing has been actively studied in the field of Artificial Intelligence. My research is mainly focused on applying machine learning methods in Information Retrieval, Text Categorization, Sentiment Analysis, Text Segmentation, Text Summarization, Privacy Policy Analysis, and Text Mining.
My research is designed to better understand the relative risks that environmental stressors may pose to the biota of aquatic and terrestrial ecosystems with the goal of improving scientific and public understanding of those risks.
Graduate students joining my team at Guelph get unrivalled opportunities to work in the lab and field answering research questions at the cutting edge of science with direct environmental and societal relevance. This important research is exciting, challenging and rewarding for the student, for me as the supervisor and for everyone else in the team.
Landscape architecture has a long history at the University of Guelph, and we are able to tap into the diversity of disciplines here in order to make a broad contribution to our students' education and experience.
My lab studies lung disease in horses, cats, and dogs. We look for relationships between air pollution and the incidence of asthma. As well, we are developing more detailed ways of understanding how lung diseases arise, and finding more accurate methods for diagnosing them.
I employ a quantitative approach to integrate observational, experimental and synthetic data sets, gathered by myself and others, to study this interaction of dispersal and environmental processes...
