Teaching

Statistical modeling and data analytics are essential skills required to future industrial engineers, especially in this big data era. These techniques include traditional quality control and improvement methods such as the design of experiments (DOE) as well as more modern predictive modeling techniques. After I joined MU, I have taught ISE 8110: Design and Analysis of Engineering Experiments, which is the core course for ISE graduate students, STAT 4750/7750: Introduction to Probability Theory, ISE 3110: Probability Models for Engineers, and STAT 4560/7560: Applied Multivariate Data Analysis. As a teacher, my goal is to have students practice fundamental knowledge and skills required to their own levels and, depending on the subject taught, deeply understand what they learned by allowing them apply such knowledge and skills to their own research or projects.