This course introduces both the classical and the latest results
from the data management and database research. Some of the
topics we will cover include I/O efficient data structures and
algorithms, indexing for multidimensional data, such as the
popular R-tree and kd-Tree, streaming data, graph data, various data
management systems and platforms, etc. We will take a balanced
approach focusing on both the algorithmic and the system aspects
of problems in data management and databases.
undergraduate computer science background is required for this
class. General knowledge on algorithms, statistics, and
probability theory is necessary. Student expects to learn an
overview of various topics in data management and database
research, especially on the issue of scalability, efficiency,
and data models. The format of the seminar will be very
flexible. The instructor will lead the discussion for 1/3 to 1/2
portion of the semester, and students will share the
responsibility of leading the discussions for the rest of the
semester, using selected papers (assigned by the instructor with
the consideration of individual interest).
Instructor: Feifei Li
Email lifeifei AT
Office: MEB 3464
Office hours: by appointment
9:40-11:00 AM on Wed; MEB 3147
No required textbook. Reading materials will be distributed when necessary.
Most of the course materials, including the syllabus, lecture
notes, reading assignments, etc., will be
available through the course Web page (http://www.cs.utah.edu/~lifeifei/cs6931/).
Syllabus in PDF format: