IE 401 Introduction to Operations Research I: An introduction to the deterministic optimization methodology of mathematical problem formulation and solution strategies.

IE702 Integer and Nonlinear Programming: Graduate course addressing mathematical foundations of integer programming and nonlinear optimization techniques.

IE 703 Supply Chain Management: Graduate course presenting concepts in transportation, inventory control, facility location, information systems and their interaction.

IE 742 Artificial Intelligence Applications: Graduate course in the development and application of "intelligent" (knowledge-based) systems.

IE 787 Systems Optimization: Executive Graduate course dealing with the interaction of operations management and systems.

IE 335 Introduction to Operations Research I: Introduction to deterministic optimization modeling and algorithms in operations research. 

IE 490G Computer Graphics: Undergraduate/Graduate course exposing students to Computer Graphics and a number of applications in Industrial Engineering.

Big Data Optimization (University at Buffalo). This course will introduce the definition of “Big Data” (Volume, Velocity, Veracity and Variety) as input to optimization problems. The course will look at the workflow of heterogeneous data types (structured and unstructured) as they progress in a flow of phases (i.e. semantic augmentation, homogenization and analytics). Both, batch and streaming analytics will be studied and create an understanding on the type of methods that will be proven successful for certain characterized problems.

High Level Information Fusion (University at Buffalo). This course will introduce High Level Information Fusion concepts and methods to give students a good understanding of this new area of research that is the combination of multidisciplinary classical fields of research. This course will give a brief introduction of a number of Fusion Models and how its different subcomponents interact with each other. The course will focus on Information Fusion as it relates to Situational Awareness/Understanding, Impact/Threat Assessment and Process Refinement (which is called High Level Fusion in one of the models we will be studied).

Discrete Optimization (University at Buffalo). This course is a natural continuation to Linear Programming to give students the basic tools in the areas of Integer Programming and Network Optimization. The course was developed with the intention of given students in the areas of production, manufacturing and operations research the necessary tools to solve discrete phenomena that arise in a number of practical problems in industry.

Design and Analysis of Algorithm (University at Buffalo). This course was design for advanced Master Students and Ph.D. students. Different than Computer Science courses in this area, the emphasis is Computational Complexity and Heuristic Optimization rather than exact Algorithms.

Introduction to Artificial Intelligence (University at Buffalo). The course was developed for seniors and graduate students interested in the principles of Artificial Intelligence and Expert Systems. The course used LISP language as a learning tool for Artificial Intelligence concepts.

Supply Chain Management (Rochester Institute of Technology). The course was developed for undergraduate and graduate students in Industrial Engineering as well as part of a graduate program in Product Development. This course introduces students to the concept of logistic management and its integration with applied operations research.

Computer Graphics (Purdue University). This course was developed for senior undergraduate and graduate students with interests in interfacing Computer Graphics with a number of Industrial Engineering applications.