Basic probability (ECE 313 or equivalent), introductory knowledge of machine learning or instructor’s consent, and basic computer systems knowledge.


We will compute the final grade using the following table:

Activity Grade Details
Paper Reviews 10%
Student-led Presentation and Discussion 15%
Class Participation 5%
In-class Design Innovation Activity 30%
Course Project 40% Proposal (3%) + Prelim Presentation (7%) + Mid-term Report (10%) + Final Report (10%) + Final Presentation (10%)

Credit Policy

  • Student attendance in all lectures is required.
  • Full credit for submissions on time.
  • Late submission policy: 10% will be taken off for every day, prorated up to 3 days max (0 credit after that).
  • While we encourage discussions, submitting identical material is not allowed and will incur appropriate penalties.

Paper Presentation & Reviews

The instructors will use Campuswire as a medium for paper discussion. For each regular class, students who are not presenting in that session are expected to write short reviews for the papers being presented by 10:00pm the night before the class. Please try to engage in a discussion with your classmates instead of summarizing the paper.

For Reviewers
  • Description: 1 paragraph on the core idea of the paper, followed by list of pros and cons of the approach, and any questions/criticisms/thoughts about the paper.
  • Grading Criteria: Argumentative critique (Pros/Cons), Creative comments about addressing issues or improving the paper.
  • Due: Night before class at 10 p.m. Link will be posted on Campuswire.
For Presenters
  • Sign-up: TBD
  • Description: 10-12 slides max (20 min for paper). 2-3 slides on motivation and background. 3-5 slides on core ideas of the paper. 2-4 slides on experimental data.
  • Due: Slides due night before class at 10 p.m.
For Discussant
  • Sign-up: TBD
  • Description: 3-5 slides max (7 min for discussion). Slides should include your thoughts/criticisms/questions/discussion points about the paper. Include slides summarizing Campuswire discussion about paper.
  • Due: Slides due before class at 10 a.m.

Course Project

The final project is an open-ended research project that can target the design, development of reliable systems and networks. Projects dealing with evaluation of systems reliability using analytical models or measurements are also encouraged. We will also provide a list of project topics for reference, but you are free to come up with your own ideas.

Project Team Signup

Students will form groups of two or three for the final project early in week 3. One member of each project team should signup the team at this (link TBD) by (date TBD) before the start of the class. We will also initiate a Campuswire post to help you in team search. Failure to form project group by the deadline will lead to TA assigning the student to a group.

Project Requirements
  1. Initial project proposal and presentation
  2. Two reports
  • Mid-term Report: A short presentation to report on your initial progress including a critique of the literature.
  • Final Report: Encompassing initial goals, results achieved, method/approach, major accomplishments.
  1. Final presentation
Project Ideas

To be announced.