Courses Taught by Institute

Management Department, School of Business, New Jersey City University, Jersey City, NJ

  • BUSI 213 Business Statistics (Fall of 2015; Spring of 2016) – Undergraduate

Designed to acquaint the student with basic business statistics, this course includes the following topics: measures of central tendency and variability; probability; hypothesis testing and correlation; and regression analysis. Prerequisite: MATH 1165 Pre-Calculus for Business

  • MGMT412 Business Information Systems  (Fall of 2015; Spring of 2016) – Undergraduate

This course provides an integrative study of what constitutes management information, goals of management, and measures of information value in support of those goals and usual sources of information. The course reviews how management utilizes the vast amounts of computer-generated data.

  • MGMT413 Global Supply Chain Management  (Fall of 2015; Spring, Summer, & Fall of 2016) – Undergraduate

This course is designed to acquaint students with basic concepts of global supply chain management. The course includes balanced topics on operations and marketing including sourcing, logistics, information technology, and supplier relationship management.

  • MGMT511 Seminar: Management Science  (Spring of 2017) – Undergraduate

This course offers the rationale for applying certain models to managerial problems, assists students in the application of such models and guides students in the interpretation of results. The course includes basic quantity techniques used in managerial decision making. The topics covered include: linear programming, queuing, network analysis, inventory models and decision making under uncertainty. Prerequisite: BUSI 203 Business Statistics; MGMT 211 Principles of Management

  • BUSI612 Global Strategic Management  (Summer of 2016) – MBA
  • BUSI613 Decision Analysis  (Summer of 2016) – MBA

Department of Industrial and Manufacturing Engineering, North Dakota State University, Fargo, ND

  • Operations Research I (IME470/670)

Techniques to optimize and analyze industrial operations. Use of linear programming, transportation models,     networks, integer programming, goal programming, dynamic programming, and non-linear programming.

  • Logistics Engineering and Management (IME451/651)

The course is an introduction to and survey of the various logistics and supply chain issues that today’s organizations must address to remain competitive in a business climate increasingly shaped by information, speed, and flexibility

  • Quality Assurance and Control (IME460/660)

This course provides an introduction to statistical tools and techniques available for defining, monitoring, and improving quality and reliability of products, processes, and services.  Topics include statistical control charts, process capability analysis, acceptance sampling, and application of design of experiments for product and process optimization.  If time permits, Taguchi methods and reliability estimation will also be briefly covered.

Transportation and Logistics Program, North Dakota State University, Fargo, ND

  • Context Sensitive Solutions (TL755)

Context Sensitive Solutions (CSS) examine, in addition to traditional transportation engineering factors, impacts on the community as well as the natural and human environment. This course will introduce students to the main principles of CSS and allow them to learn how they are applied through use of case studies.

  • Transportation Planning and Environmental Compliance (TL752)

This course provides an overview of the procedures of transportation planning and environmental compliance, to include an understanding of the related policies and procedures as they relate to transportation systems, and compliance with local, state, and federal laws. A discussion of emissions, hazardous cargo, and permitting also will be provided.

  • Transportation System Modeling (TL753)

This course focuses on quantitative techniques used for planning and operation of transportation systems. Topics include: system capacities and flows, comprehensive models of transportation and urban systems, and understanding how political processes, new technologies, and economic considerations affect transportation decisions.

  • Spatial Analysis in Transportation (TL785)

This course focuses on applications of Geographic Information Systems (GIS) to transportation networks and problems. The emphasis is on data modeling. Topics include: linear referencing, dynamic segmentation, network analysis, urban and land use planning, routing of hazardous materials, and asset management applications.

  • Geospatial Information Systems in Transportation (TL885: Summer of 2017)

This course focuses on spatial analysis in transportation using Geographic Information Systems to build research framework and solve problems in transportation and logistics. The emphasis is on data modeling and the cutting-edge theories.