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Ontario Tech acknowledges the lands and people of the Mississaugas of Scugog Island First Nation.

We are thankful to be welcome on these lands in friendship. The lands we are situated on are covered by the Williams Treaties and are the traditional territory of the Mississaugas, a branch of the greater Anishinaabeg Nation, including Algonquin, Ojibway, Odawa and Pottawatomi. These lands remain home to many Indigenous nations and peoples.

We acknowledge this land out of respect for the Indigenous nations who have cared for Turtle Island, also called North America, from before the arrival of settler peoples until this day. Most importantly, we acknowledge that the history of these lands has been tainted by poor treatment and a lack of friendship with the First Nations who call them home.

This history is something we are all affected by because we are all treaty people in Canada. We all have a shared history to reflect on, and each of us is affected by this history in different ways. Our past defines our present, but if we move forward as friends and allies, then it does not have to define our future.

Learn more about Indigenous Education and Cultural Services

October 22, 2014

Speaker: Dionne M. Aleman, Department of Mechanical and Industrial Engineering, University of Toronto.

Title: Distributed Computing Methods for Large-Scale Health-care Decision Making

Abstract: Medical decision-making requires the analysis of many factors - frequently more than can be adequately interpreted by a human. Medical decision-makers have therefore increasingly turned to mathematical optimization to consider all available information and provide an optimal course of action. However, optimization is limited by computer resources and algorithm sophistication. In this research, we harness advances in parallel and distributed computing technology to solve complex, large-scale health-care problems that are unsolvable by current methods on a single computer. In particular, we focus on applications in radiation-therapy treatment planning and on pandemic modeling and planning.