Lecture: 1 hour

Prerequisite: Graduate standing in computer science

Grading: S/U; projects (50%), classroom participation (50%)

Catalog Description:
Study of research topics in computer science, PhD level research methodologies (experimental, applied and theoretical). Study skills necessary to successfully find/solve significant research problems. Finding and successful interacting with a research advisor. Ethical issues in research/collaborative work.

Expanded Course Description:

  1. What makes a good research area and topic
  2. Major research topics in computer science (this is the majority of the class)
    1. Theory: cryptography, computational geometry, computational biology, optimization, scientific computing
    2. Systems: security, software development, distributed systems, high performance
    3. Networking: optical, wireless, sensor, protocols
    4. Architecture
    5. Graphics and Visualization
    6. Information Systems
    7. Artificial Intelligence
  3. Choosing a Research topic
  4. Picking an advisor
  5. Ethical issues in classwork and research


Selected articles and Web sites

Computer Usage:

None required

Instructor: C.U. Martel

Prepared by: C.U. Martel (October, 2006)

Overlap Statement:

Slight overlap with 293B in the introductory part of the course. The focus on computer science research makes this course substantially different from orientation classes in other fields.