Introduction to Modelling

Undergraduate / Graduate

This class presents applications of mathematics to biology, chemistry, economics, engineering, and physics. Students work in groups to explore mathematical and computation tools. The course consists of a sequence of modules, one for each key concept. Each module consists of roughly three lectures. The first lecture briefly explains the motivation and practical context before quickly moving to describe the methodology and mathematical notions. The second lecture explains the heart of the modelling process. The third lecture solves the problem. Examples of mathematics that will be included are dynamics (discrete, continuous (ode), spatial dependence (pde)), optimization (linear programming, dynamic programming), discrete probability, and statistics (data analysis). Examples of models are problems from biology, ecology, economics, finance, physics (atomistic models, electric circuits), mechanics (bars under tension), car traffic, tracking problems, astronomy, etc.