Canada Research Chair in Industrial and Applied Mathematics
Tier 1 - 2001-07-01
Natural Sciences and Engineering
Studying the dynamics of differential equations that arise from population biology and neural networks.
Findings will provide theoretical mathematical foundations that can be used to predict the long-term status of ecological systems and to develop neural networks architectures to analyze patterns in large data sets.
Clustering Data and Protecting Ecosystems Through Mathematics
How can scientists predict the long-term status of an ecosystem comprising interacting and competing species, which continue to move around in search of limited food and resources? What factors might lead to the extinction of, or to an infectious disease outbreak in a particular species? How can neural networks - systems that work like a human brain, learning to "think" and solve difficult problems based on previous experiences - be used in data mining applications, such as collecting and filtering through massive amounts of correlated information to find patterns?
These are just some of the questions Dr. Jianhong Wu's research seeks to answer. Dr. Wu is an internationally recognized mathematical authority in delay differential equations, infinite dimensional dynamical systems, non-linear analysis, mathematical biology and neural dynamics. His award-winning contributions continue to play a key role in advancing scientific research and development, and in assisting industry through "real-world" applications. Dr. Wu has published four major books and over 140 research papers in peer-reviewed journals, which are highly valued among scientific and industrial communities.
Dr. Wu is now using Canada Research Chair funding to conduct comprehensive, multidisciplinary research in industrial and applied mathematics. He and his expert team are interacting and collaborating with university researchers in related fields, and with industrial data mining experts. Together, they are analyzing the information processing capabilities of neural networks modelled by differential equations to develop effective mathematical formulas and software for pattern recognition, classification and prediction. The team will also work with industrial partners to assess the effectiveness of their research discoveries in solving actual data analysis tasks.
Dr. Wu's work will advance theoretical research in mathematical modelling and analysis for neural networks and should lead to novel applications that improve the global competitiveness of Canada's data mining industry.
Wu will also contribute to the International Research Chairs Initiative (IRCI), a new partnership between the International Development Research Centre and the Canada Research Chairs Program.