Dynamic or sequential decision-making tackles a type of problems where decisions need to change over time to adapt to changing environments, occurring as a consequence of natural environmental dynamics and/or influence of prior decisions. These type of problems are encountered in a variety of fields.

With the advancement of technology, the world is becoming increasingly data rich. Engineers are expected to use large quantities of data as they design and evaluate systems. However, these large amounts of data cannot inform decisions until they are statistically analyzed for patterns and translated into insight. This course will discuss and use the field of probability and statistics to demonstrate its importance and utility in the solution of problems specifically of interest to industrial engineering and engineering management.

Theory and application of linear programming. Includes formulation of linear programming models, simplex, revised simplex and dual simplex algorithms, duality, parametric procedures, interpretation of results, and the decomposition principle. Prerequisite: consent of instructor.

The course is under the umbrella of the Materials Group and the Biomechanical Engineering Group in the Department of Mechanical and Industrial Engineering. The course will cover functional nanomaterials and biosensors based on the nanomaterials.

This course will cover both fundamental and cutting-edge topics in robotics. We will study the kinematics, dynamics, and autonomous control of various robotic systems (e.g., manipulators, mobile robots, and exoskeletons). The fundamentals will be studied in lectures and robot simulation exercises. State-of-the-art robotics research will be studied through paper reviews and discussion. A final research project will allow you to dive deeper into your choice of a topic covered in this course.

Structuring of materials at the micro-/nano-scale has become a standard method for creating optical, thermal, acoustic, and mechanical properties, which are not possible by traditional stochastic material processing. The new materials created by the deliberate control of their structures have been called ?metamaterials? and will play a critical role in developing future high-performance materials. The course aims to provide multidisciplinary knowledge for understanding metamaterials with selected applications.

Principles of mechanical behavior and failure of metals, polymers, and ceramics. Analysis of problems in design of structural materials that must meet certain strength and performance criteria. Emphasis on the engineering significance and use of various experimentally measured properties such as fatigue life, critical stress intensity factor, relaxation modulus, creep rupture life, and crack growth rate.

The course provides advanced background to fluid mechanics including statics, kinematics, governing equations of fluid flow, viscous flow, inviscid ideal flow and gravity waves.

This course will cover use of computational fluid dynamics codes, code structure, and mathematical background. Advanced topics, such as turbulence modeling and compressibility, will also be discussed. Prerequisite: M&I-ENG 603 Numerical Methods (or equivalent).

Numerical methods of solving problems in engineering analysis. Topics include interpolation polynomials, numerical integration and differential equations, multiple regression and correlation, roots of equations and solution of simultaneous equations and numerical solution of partial differential equations. Prerequisites: undergraduate calculus and differential equations.