Role: Instructor.

Description: This course covers the basic concepts of engineering economy including time value of money, equivalence, replacement analysis, equipment selection.

Syllabus: (Subject to change)

Textbook: Chan S. Park, Contemporary Engineering Economics (5th Edition), Prentice Hall, 2010.

Role: Instructor (Teaching Assistant).

Description: This is an introductory course in probability theory & Statistics that is designed for engineering and science major students. It covers data analysis, the role of statistics in engineering, introductory probability concepts, discrete and continuous random variables and probability distributions, joint probability distributions, random sampling and data description, point estimation of parameters and statistical intervals for a single sample.

Syllabus: (Subject to change)

Textbook: Jay L. Devore, Probability & Statistics for Engineering and the Sciences (8th Edition).

Role: Teaching Assistant.

Description: This course is designed to focus on the concepts, principles, and methods of experimental design (DOE). It offers a systematic introduction of major principles and methods in DOE, including: design principles, hypothesis tests, ANOVA, ANCOVA, Latin Square, Factorial Design, 2^k, Regression, and data analysis. Students learn how to solve DOE problems using Minitab and SPSS.

Role: Teaching Assistant.

Description: Revenue Management (RM), or Yield Management, is a set of operational tools for generating more revenue with resource allocations and/or dynamic pricing. In this course, we will cover the fundamental concepts of RM, with mathematical models and algorithms, including capacity control, network capacity control, overbooking, dynamic pricing, customer choice modeling, pricing under competition, estimation and forecasting. By the end of this course, students will be able to understand the basic principles of RM, build mathematical models and suggest proper computational solution methods.

Role: Teaching Assistant.

Description: This course will be an intensive study of Linear Programming (LP). LP deals with the problem of minimizing or maximizing a linear function in the presence of linear equality and/or inequality constraints. Both the general theory and characteristics of LP optimization problems as well as effective solution algorithms and applications will be addressed. Students learn how to use an optimization software tool called OPL/CPLEX to solve LP optimization problems.

Role: Teaching Assistant.

Description: Facilities Design teaches the analytical tools necessary to effectively tackle problems related to a typical manufacturing and/or warehouse facility. These include plant layout, warehouse design, facility location, routing of material handling shipments, and automated guided vehicle systems. The primary focus of the course is on quantitative methods.