Our group is recruiting year-round for postdocs, MASc and PhD students, visiting students and undergraduate students. Please see our Opportunities page for more information.
The course is divided into two main parts – a first part that deals with modeling, representation of models in Laplace domain, analysis of transient response, and a second part that deals with design of feedback control systems, analysis of closed loop stability and frequency response. This is one of the largest undergraduate courses in our department and typically has over one hundred students.
This is an undergraduate laboratory for third year students. This lab complements the theory taught in unit operations courses. There are typically about eighty students from process, biotechnology, and environment options.
This is a follow-up undergraduate laboratory for third year students in the process option. The students perform experiments on unit operations. This course typically has an enrollment of about forty students.
This is a unique laboratory course that was designed recently in our department. In conventional labs, students are given a set of pre-defined instructions on how to perform experiments. In this lab, students perform problem-based experiments that are open ended. Students are given a real- life problem, and asked to form a team of engineers to design and implement a solution. This course typically has an enrollment of about eighty students.
This is a higher level undergraduate course typically offered to the fourth year students. This course covers advanced control topics that include cascade, feedforward, nonlinear, adaptive, and fuzzy control systems. The course also introduces students to multivariable control systems such as model predictive control.
This is a graduate level course on thermodynamics of chemical engineering systems. The topics include, pressure-volume-temperature relations; chemical equilibria by Gibbs’ method; vapor-liquid equilibria; thermodynamic calculations by third law and quantum-statistical methods; irreversible thermodynamics and information theory.
This is a graduate level course on engineering optimization. The course is divided into two main parts – the first part deals with formulation of optimization problems, in particular convex optimization problems, and in the second part, algorithms for solving optimization problems are discussed. This course introduces students to a number of standard optimization problems in modeling, design of experiments, and statistical inference. This is one of the largest graduate courses in our department with an enrollment of 28 students in the academic year 2008-2009, and about 20 students in 2010-2011.
This is one of the core graduate courses on numerical techniques in chemical engineering. It covers techniques for solving linear and nonlinear algebraic systems, ordinary differential equations, partial differential equations, and basic concepts in probability, time series analysis and experiment design. This course typically has an enrollment of about twelve to fifteen students.