Graph analytics have applications in a variety of domains, such as social network and Web analysis, computational biology, machine learning, and computer networking. This course will cover research topics in graph analytics including algorithms, optimizations, frameworks, and applications. Students will learn about both the theory and practice of designing efficient graph algorithms (parallel, cache-efficient, external-memory, etc.). We will also study design choices in high-level graph processing frameworks.