Tracking The Mind: Measuring Social Media Behaviour
Professor Ding received her BSc. and MSc. degree from Nanjing University and PhD degree from the National University of Singapore. She joined the Department of Computer Science at Ryerson University in 2003, where she holds the rank of professor.
Her research interests are in the areas of service computing, data analytic services in the cloud, recommendation systems, social network analysis, and Quality of Services.
Currently, a primary focus of her work is on cloudbased service selection and recommendation, and behavior analytics for social networks, such as Facebook. Her current research projects, funded by Natural Sciences and Engineering Research Council of Canada and Canada Foundation for Innovation, examine quality recommendation for software service provisioning and QoS-based web service selection and ranking.
Dynamic Systems in AI: Reasoning about Actions and Events
AI is a broad activity that includes several exciting research areas. One of the key issues is how creative human problem solving can be automated within the available computational resources. Mikhail Soutchanski works in this direction using a principled approach to reasoning about actions.
Using this approach problem solving can be represented symbolically in a logical language. Soutchanski works both on foundational problems in AI and on practical applications of AI. The research directions include computing actual root causes of observations from traces of events, developing new efficient lifted planning teachniques for solving practical problems, and planning in hybrid systems that contain both continuous and discrete components. His students design efficient algorithms for solving some of the feasible instances of the planning problem, and develop prototype implementations.