Design principles of secure systems, authentication, access control and authorization, discretionary and mandatory security policies, secure kernel design, and secure databases.

Teams or individuals apply the knowledge and skills acquired throughout the MS program to a faculty supervised robotics project.

The course explores GPU software and hardware, covering GPU programming, optimizations, GPU architecture, compiler techniques, and performance analysis.

The course explores GPU software and hardware, covering GPU programming, optimizations, GPU architecture, compiler techniques, and performance analysis.

Describes the characteristics of interaction between humans and computers and demonstrates techniques for the evaluation of user-centered systems. 

Computational machine models and their language classes. Undecidability. Resource-bounded computations. Central complexity-theoretic concepts such as complexity classes, reducibility and completeness.

Topics of current interest in Computational Science and Engineering.

This project-based class offers students the opportunity to critically analyze learning in video games and to design and prototype educational games.  Students will gain insights into perspectives and theories of how people learn and how those theories map to video games. They will explore game mechanics to evaluate their usefulness in promoting learning. Building on these understandings, students will design learning games through several low-fidelity prototypes and a final team-based project to promote learning.  

This course teaches operating system abstractions, mechanisms, and their implementations, including for concurrency (threads) and synchronization, resource management (CPU, memory, I/O), and distributed services.

An introduction to artificial intelligence and machine learning. Topics include intelligent system design methodologies, search and problem solving, supervised and reinforced learning.