Study of computer science techniques and tools that support computational sciences and engineering. Emphasis on visualization, performance evaluation, parallel computing, and distributed computing.

This course covers the fundamental concepts involved in understanding and engineering a closed- loop, sensing, reasoning, and actuating agent. Biological models of sensing and actuation will be discussed and related to modern artificial counterparts. The course consists of three major topic areas: vision, brain, and robotics.

The course covers fundamentals of propositional and predicate logic, and their uses in declarative programming to model and solve computational problems. Topics include propositional satisfiability, satisfiability testing techniques such as the DPLL algorithm, automated reasoning techniques for predicate logic such as resolution with unification and logic programming.

The course examines the requirements phase of the Sys- tems Engineering and Software Engineering lifecycles in detail. Topics include: requirements elicitation, requirements specification, and requirements analysis. Verification and validation techniques are emphasized throughout the course. Students work in small groups to research and present a related topic.

The course will present advanced computational science techniques needed to support large scale engineering and scientific computations. Emphasis on iterative methods for solving large sparse linear systems and parallel implementations of iterative techniques.

This course covers the path from a conceptual vision of a shape to a concrete computer-based description that is suitable for manufacturing. It covers various solids modeling techniques, including volume representations, boundary representations, instantiation and Boolean combinations of shapes, and procedural generation such as sweeps.

Overview of current concepts and issues in CAGD with emphasis on free-form surface design; mathematics of free-form curve and surface representations, including Coons patches, Gregory patches, Bezier method, B-splines, NURBS, triangular interpolants, and their geometric consequences; creating objects with smooth surfaces, covering assembling spline patches, geometric and parametric continuity, texture mapping onto complex shapes, subdivision surfaces, surface evolution, and global optimization.

This course covers fundamental techniques in multimedia systems for capturing, managing, accessing and delivering digital media over local, wide-area and wireless network technology. The core topics will emphasize the digital media (images, video, audio) and the algorithms to generate, store, access and process it. Network concepts will be presented at a high level only.

This course covers a mixture of core techniques related to systems for constructing and modeling virtual environments, such as model- building, image-based rendering, head-mounted hardware, stereo image generation, head- tracking, and immersive display technology. The core topics will be presented using textbooks and papers from the current literature. A substantial group project will provide hands-on experience with the concepts, algorithms and technology.

The objective of the course is to prepare students for research in the field of supervisory control of discrete event systems (DES's). Logical models, supervising control. Stability and optimal control of DES, complexity analysis and other related research areas will be covered.