APPROACH
The central tenet of my teaching philosophy is to deliver the technical engineering skills component with a focus on the engineering impact on society and the environment.
I use active learning techniques and group activities to create an engaged classroom.
COURSES
CIVL 3120 Hydraulics: This course focuses on fluid flow including flow in pipes and open channels, under laminar and turbulent conditions, in steady or unsteady conditions, and flow through and past various objects. The course covers the equations of motions for fluids, differential fluid flow analysis, potential flow theory and the boundary layer approximation.
CIVL 3220 Hydrology: The course introduces basic hydrological processes such as precipitation and abstractions. It also covers engineering applications such as statistical hydrology, regional frequency analysis, water balance methods, the unit hydrograph and rainfall-runoff processes, flow routing techniques, and urban hydrology.
Winter 2018: CIVL 4022 Water Resources Engineering: This course focuses on the advance principles of engineering hydrology and hydraulics and applies them to various water resource engineering systems with a focus on sustainability and environmental integration. The course will review basic hydrology and hydraulics engineering principles and introduce sustainable water resource management and planning, including: Groundwater and surface water processes; Watershed runoff simulation in rural and urban settings; Numerical simulation of water resources systems; Urban hydrology, water distribution and stormwater management systems; Extreme event analysis, risk & uncertainty for hydrological and hydraulic design; Water-use and stresses in agriculture, industry, domestic, recreation and ecological needs; Water markets and economics of water resources management.
CIVL 6620 Data-driven modelling and uncertainty analysis: This course will introduce and develop advanced engineering, mathematical and statistical techniques for modelling water resource systems and to quantify the uncertainty of these modelling technique. The course includes 3 modules related to data-driven models (model development and performance testing), statistical methods (hypothesis testing, Bayesian analysis), and fuzzy set theory (fuzzy arithmetic, fuzzification techniques).
