Dr. Yang’s teaching activities at Old Dominion University (ODU) extends his interests in transportation, modeling and simulation, and data analytics. Following is a list and description of the courses Dr. Yang has been teaching in the past few years at ODU:
Course Description: This course will provide an introduction to analysis techniques appropriate to the conduct of modeling and simulation studies. Topics include input modeling, random number generation, output analysis, variance reduction techniques, and experimental design. In addition, techniques for verification & validation are introduced. Course concepts are applicable to real systems and data sets. Extensive examples and hands-on exercises will be included in the class.
Course Description: The advance in transportation systems resulted in the generation of massive data (e.g., vehicle trajectories, loop detector data, real-time use of bike-sharing systems, social media data related to transportation, etc.). This course is designed to introduce students the basic techniques of data analytics for leveraging the values of these data. The course covers statistical modeling and prominent algorithms to mine various types of transportation data. It is targeted towards individuals who would like to know the practices of using different data for various traffic/transportation applications and decision makings in real world. The goal of this course is to ascertain that the students know the techniques and tools frequently used to analyze different types of data. In addition, it intends to teach students the skills to go beyond the transportation engineering and can work with various data in other fields.
Course Description: An introduction to stochastic dependence and Bayesian analysis techniques for conducting modeling and simulation studies. Topics include: measures of dependence, common multivariate distributions, sampling from multivariate distributions, elementary time series models and Bayesian statistics.