Teaching
Undergraduate
ESM2009 Applied Statistics I: Theory and Practice
This course introduces basic concepts of probability and statistics, descriptive methods for data analysis, random variables, probability distribution(discrete and continuous), and Normal distribution. Students taking this course are required to participate a problem solving practice session one hour per week. This course is a gateway course to all the courses offered by School of System Management Engineering.

ESM3023 Simulation: Modeling and Practice
Simulation is a powerful OR/MS tool for scientific decision making in various fields. In this course, we learn the simulation methodologies, such as Random Number Generation, Output Analysis techniques, Variance Reduction Techniques. We spend substantial amount of class hours to learn a computer simulation language, ARENA. Basic concepts of Queueing Theory and Statistics are required, but not mandatory. Students are asked to participate several simulation projects, out of text and/or real situation.

ESM3054 Business Forecasting: Methodology
Forecasting under uncertain business environment is a starting point for all managerial activities. General forecasting methodologies, simple linear regression and new service forecasting methodologies will be discussed in this class. A forecasting software(SmartForecast) will be used and a term project of real problem is required.

Graduate
 ESM5018 Seminar in Management Engineering
This course deals with key ideas of management innovators. Major topics include F.W. Taylor's scientific management, E. Mayo's Hawthorne effect, H. Ford's mass production system, W.E Deming's quality management, T. Ohno's just-in-time Production, M.Hammer's reengineering, P.Senge's learning organization, M.Porter's competitive strategy, etc.

ESM5009 Discrete Event Simulation
Simulation is a powerful OR/MS tool for scientific decision making in various fields. In this course, we learn the advanced simulation methodologies, such as Random Number Generation, Output Analysis techniques, Variance Reduction Techniques, and Fast Simulation techniques. We spend substantial amount of class hours to learn a computer simulation language, ARENA. Students are asked to participate several simulation projects, out of text and/or real situation.

ESM4025 Experimental Data Analysis
 Exposition of the philosophy and tools of exploratory data analysis. Tools include graphical techniques, data transformation, robust and resistant summaries, residual analysis, and resampling methods. Application to the analysis real data sets, stressing alternative analysis using software.

ETM5030 Market Research
This course focuses on the application of research methods designed to obtain information for data collection, and interpretation of information to provide customer orientation in MOT business.      

DMR5009 Market Analysis and Prediction for medical device
 This course will provides students with a advanced knowledge and practice of market analytic techniques within medical device industry. The primary goal of this course is to understand the major concepts in market analysis that will enable students to make decision in medical device industry. Students will develop the market analysis skills which are required to medical device industry as finding, analysing, and solving the various problems in the field through case studies and discussion