CSCI 7000-002 Fall 2010
  
Systems and Algorithms for Massive Data Applications

Announcements

Administrative Information

Meeting time Tu Th 09:30am -- 10:45am
Location ECCS 1B12 map
Instructor Qin (Christine) Lv
Phone (303) 492 - 8821
Fax (303) 492 - 2844
Email
Office ECCR 1B05C
Office hours Tu 11:00am - 12:00pm or by appointment.

Course Description

This course presents a survey of recent research on efficient system and algorithm design for managing and exploring massive amounts of digital data. This course covers systems issues such as search systems, storage systems, peer-to-peer systems, mobile and sensor networks, as well as practical use of sketching, indexing, and data mining techniques. Domain-specific data management and analysis, such as those in finance, health, multimedia dan, online social networks, bioinformatics, and scientific computing, are also covered.

This course is open to both PhD students and MS/ME students. Students are expected to read research papers, write paper reviews, participate in discussions, present papers, and finish a course project.

Course Schedule

Please see the internal course website for the most up-to-date schedule.

Grading

Your performance will be measured in the following four ways:

Paper review (30%)
There are 2-3 papers in the readling list for each class. You need to pick at least 15 papers from the lists and write a review for each of them. Your review may contain the following: what is this paper about? what are its strengths and weaknesses? is the description of the main technique clear to you? are the evaluations (if any) reasonable and convincing? can you improve their technique or apply it to a different domain? ....

Class participation (20%)
Besides the paper you reviewed, you should also read other papers in the reading list and be prepared to participate in discussions at class.

Paper presentation (10%)
During the semester, you will be asked to give two presentations. Each presentation is about 45 minutes long. Check out the current course schedule and pick a topic that you would like to present. You may also suggest new topics/readings. Each presentation also counts as a paper review, i.e., you do not need to submit a paper review for the topic you are presenting.

Course project (40%)
Each student needs to finish a course project that is related to the topics coverd in the course. Students can pick their own projects. Project proposals are due in Week 7. Project checkpoints are in Week 11. Final project presentations and reports are due in Week 16.

Prerequisites

Graduate standing.

Textbook

No textbook is required. A list of research papers and other reading materials will be provided.


Copyright© 2010. All rights reserved.