Current Teaching Duties

APM395/595: Probability and Statistics for Engineers

Fall Semesters

This course provides a rigorous introduction to calculus-based probability and statistical theory, with applications primarily drawn from engineering and the environmental sciences. Topics include: descriptive statistics and data presentation, probability, the theory and use of discrete and continuous probability distributions, confidence intervals, classical and distributional hypothesis testing, and regression analyses. This course also provides an introduction to the computing package R. 

Prerequisite(s): one year of Calculus.

APM595: This course meets one extra hour a week to provide an introduction to advanced statistical theory and application.  Additional topics covered include: smoothing data, data transformations, random number generation, principal component analyses, first-order error analyses, L-moments, maximum likelihood estimation, parametric and non-parametric trend tests, and censored data analyses. Additional applications in R are explored. 

ERE496: Advanced Engineering Statistics.  Students in APM395 may sign up for an additional 1-credit course that covers the material presented in APM595.

Course Syllabus

ERE465/665:  Environmental Systems Engineering

Fall Semesters
 
In this couse, mathematical models of environmental systems are presented and combined with optimization procedures, decision theory, uncertainty analysis, and engineering economics to develop integrated approaches to the planning, design, and sustainable management of complex environmental systems.  Students will evaluate and present a variety of optimization algorithms for a wide range of environmental applications.  Optimization includes constrained and unconstrained linear and nonlinear algorithms, including linear programming, dynamic programming, lagrange multipliers, genetic algorithms, and simulated annealing. 

Prerequisite: one year of Calculus; Corequisite:  Probability and Statistics.

Course Syllabus

ERE445/645:  Hydrologic Modeling

Spring Semesters

Students in this course will learn about a variety of deterministic and stochastic hydrologic models, model development, and the use of computer programming to construct, calibrate, manipulate, and interpret hydrologic models. Theoretical and empirical approaches to describing hydrologic processes will be presented, including precipitation, evapotranspiration, infiltration, surface runoff, percolation, and groundwater discharge. Stochastic techniques presented will include frequency, trend, and regression analyses.

Prerequisite(s): Introductory computer programming, Probability and Statistics, one year of Calculus.

Course Syllabus

Previous Courses Taught (2008 - present)

APM395/595: Probability and Statistics for Engineers, Fall 2012, Fall 2011, Spring 2010
ERE445/645: Hydrologic Modeling, Spring 2013, 2012, 2011
ERE465/665: Environmental Systems Engineering, Fall 2012, 2011, 2009
ERE796: Hydrogeology and Biogeochemistry Seminar, Spring 2013, 2012, 2011, 2010, 2009
ERE496: Fundamental of Engineering Preparation, Spring 2011, 2010, 2009
ERE430: Engineering Decision Analysis, Fall 2010, 2008
ERE132: Environmental Resources Engineering Orientation, Fall 2010, 2009, 2008
FEG489: Engineering Planning & Design, Spring 2008