Adminsitrivia

Syllabus

  • Fundamental algorithms and data structures
  • Spatial data bases: spatial access methods, indexing, query optimization
  • High performance I/O: data servers, storage systems, remote I/O
  • Workflows
  • Data compression
  • Applications: Fluid Dynamics feature extraction and tracking, Geographical Information systems...
  • Resources: ideas for projects, sources of some of our readings.

    • We will read about 2 papers each lecture. Students will lead class presentations. The course grade will be based on these presentations, class participation, paper summaries (see Schedule and Readings), and a project. Required Background: Students should have graduate standing. A good course in algorithms is helpful. Some of the techniques will involve numerical algorithms, but the material will be self contained. Students are welcome from Departments outside Computer Science and Engineering. If you have a favorite data set or data source you'd like to work with, let me know.

    Course requirements

    Class participation and preparation (30%)
    Your grade will be based in part on your participation in lecture and your advance preparation. We will read about 2 papers for each lecture. Be prepared to ask and answer questions and to contribute to the discussions. In addition, you must submit, before lecture, a 1 page write-up for each paper assigned that lecture. You must do this for 12 of the 20 lectures.

    In class presentation (10%)
    Each student will present two of the assigned papers in class, leading the discussion. I will moderate. Be prepared to ask questions.

    Research Project class presentation (60%)
    Your class project will count toward 60% of your grade. A project may be done individually or in teams of two, and you should allow 4 to 5 weeks to complete it. See the Projects web page for further instructions, as there are four milestones with deadlines.

    Maintained by . Last modified: Sun Mar 26 10:43:58 PST 2006