Teaching

ISYE 460/560 Facilities Planning and Design

Principles and practice of the planning of facility layout and material handling equipment for manufacturing and service systems. Topics include analytical approaches in site location, facility layout, material handling, and storage systems. Discussion of systematic procedures and computer-aided techniques.

ISYE 461/561 Warehousing and Distribution Systems

Introduction to warehousing and distribution center operations and their roles in supply chains, modern material handling equipment, and algorithms involved in the design and operation of warehouses and distribution centers.

ISYE 470/570 Introduction to Data Analytics for Engineers

A broad introduction to the key analytical tools and techniques to effectively extract and interpret complex patterns found in large amounts of data. Reinforce statistic modeling skills, and develop core skills to make informed decisions. Major topics include: data manipulation and transformation, data visualization, sampling methods, classification methods, linear regression analysis.

ISYE 480/580 Simulation Modeling and Analysis

Design and analysis of industrial systems using computer simulation models. Choice of input distributions, generation of random variates, design and construction of simulation models and experiments, and interpretation of generated output.

ISYE 640 Advanced Production Planning and Inventory Control

Advanced theory and methods of inventory control systems. Underlying behavior of production systems. Modern approaches to production planning and operations management.

ISYE 660 Facilities Layout and Location Analysis

Introduction to facilities location problems and factors affecting the selection criteria. Discussion of quantitative models and algorithms to choose the location considering various costs such as transportation, inventory, and fixed cost to open and operate a facility.

ISYE 670 Data Analytics for Engineers

Applying analytical tools and techniques to effectively extract and interpret complex patterns found in large amounts of engineering data. Develop predictive modeling skills to make informed decisions on problems that occur in engineering practice. Major topics include: data visualization, modeling, classification methods, clustering, and learning algorithms.