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 in the area of mechanical and electrical engineering. It involves the development of intelligent control and estimation strategies with applications to mechatronic systems, robotics, and real-world problems.
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.
My research improves life by assessing workplace tasks and devices for end user injury potential. Once the risk is understood, new methods and devices are designed to minimize the potential of developing injuries such as carpal tunnel syndrome.
My community-engaged research collaborations focus on the interplay between citizens – particularly young women and women in northern communities – and the framing and development of public policy.
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.
Promotion of dairy cattle health, production, efficiency, and welfare not only contributes to economic viability of the dairy production sector, but also provides benefits to the consumers of milk products. These benefits include environmental sustainability, maintenance of milk nutritional quality and safety, as well as assurance that milk is sourced from animals that have been raised humanely.
