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.
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...
I am interested in the diverse knowledge systems and participatory approaches (citizen science, youth engagement, community-based monitoring, Indigenous guardians, etc.) that contribute to community-led environmental decision making in resource-based and remote communities.
The problems I have worked on in animal science have direct implications for genetic selection, food quality (e.g. cow milk), and animal health. On the other hand, my work in understanding the structure and driving mechanisms of ecological (e.g. plant-pollinator) networks have indirect implications for ecosystem conservation, management, and restoration.
Jennifer's research is concerned with the roles of institutions, markets, and technologies in environmental governance. Topically, many of her projects have centered on oceans, marine resource management, and coastal and Indigenous communities.
