Instructor: Barzan Mozafari (To ensure a timely response, ALL email inquiries regarding this course should have a title starting with "EECS584").
GSI: Rui Liu (ruixliu AT umich.edu)
There is no official textbook for this course. The reading list is a collection of papers, which will be posted on the course web page. However, students need to be familiar with the introductory-level material covered by EECS 484. Occasionally, optional readings are suggested from the following book:
EECS 584 will cover a number of advanced topics in big data, database technology, and modern data-intensive systems. The topics include advanced concurrency control mechanisms, modern query processing and optimization, advanced indexing and storage, parallel and distributed databases, map-reduce and NoSQL, database-as-a-service (DB clouds), columnar and in-memory databases, machine learning at scale, approximate query processing, and database security and privacy.
In addition to learning advanced topics in data management and data-intensive systems, this course will provide the students an opportunity to practice important research skills:
The prerequisite for this course is EECS 484, equivalent coursework, or permission from the instructor.
Note: To pass this course, you need to obtain at least 30% of the grade in each of these five components. For example, a score of 20% for class participation will subject you to a failing grade (at the instructor's discretion) even if you obtain a 100% score in all other components. In other words, your final grade is a weighted average of your scores in these different components only if your score is above 30% in each component.
The majority of this course will be conducted as a seminar. A typical class will include a student presentation (approximately 30 minutes) followed by a class discussion of the designated paper(s). Each student will be assigned to present a paper at least once throughout the semester. When the number of students exceed the number of papers, some papers will be presented by a team of two students. When you present a paper, your goals should be as follows:
You will need to strike a balance in your presentation: realize that there will not be time to cover all of the technical details, so you will need to decide which details are most important. Here are some additional resources that can help you prepare and deliver a good presentation:
Presentation Requirements: When it is your turn to present, you must read your assigned paper well in adavance.
To help improve the quality of the presentations, all student presenters are required to meet the instructor in his office according to the following schedule. You must prepare your draft slides and email them to the instructor prior to your practice meeting time. You must create your slides in PowerPoint using this template.
Your presentation will be evaluated based on several criteria: how well-prepared and organized your presentation is, and the extent to which you have distilled the key information of the original paper. Please refer to the grading table).
You are expected to attend all lectures (see exceptions), and more importantly, actively participate in class discussions. Even if you are not currently enrolled (e.g., undecided or on a waitlist) but may enroll before the add/drop deadline, it is your responsibility to still attend the lectures and fulfill all the class requirements.
All students, whether presentors or not, are expected to carefully read the papers before class (i.e., mandatory readings) and write a short review/summary for each paper according to the following deadline. This serves two purposes: (1) it ensures that you will be prepared to participate in class discussions, and (2) it improves your critical skills in evaluating other people’s research, and thereby your own paper writing skills.
Your reviews can be brief, but should contain the following components:
How to Submit Your Reviews: You must submit your reviews using this link only. Submission are managed through an automated system and will not be accepted after the deadline (no exceptions). Submitting reviews by emailing the instructor(s) or any other means will NOT be accepted. Once your review is submitted successfully, you will receive an automated confirmation email. Please check your spam folder if you do not receive a confirmation.
All reviews will be graded as “weak”, “average”, and “strong”. See some examples of strong, medium, and weak reviews. Reviews of each paper will be graded either by the GSI or by one of the students themselves. If you are assigned to grade a particular paper, follow these instructions to submit your grades.
Note: You are on your honor not to read or use other students' reviews before the submission deadline. Read the engineering honor code. No violation of the honor code will be tolerated. However, once the deadline has passed, you are encouraged to read other students' reviews by following these instructions to see other' perspectives and also learn about strengths or weaknesses you might have overlooked in your own review.
There will be a closed-book midterm exam based on the mandatory readings of the class. Each student must complete the exam solely by her or his own efforts. Questions during the exam can be asked only of the course instructors. The exam must be completed within the specified time. No makeup exam will be offered. Please check the midterm date and time before enrollment. See the midterm date, time and location.
A major component of this course is a class project. For this project, you form a team (see our team size policy) and choose a research topic in the area of data management, and explore it in detail. Projects can range from quite theoretical to implementation-heavy ones, and should include some original work. In other words, survey articles are not permitted. You may choose to implement an existing algorithm or technique, but this should be done in order to conduct a unique experiment, or to test a novel hypothesis. All project topics need to be approved by the instructor to avoid situations where the topic or scope is not acceptable for the final project of this course. To ensure that you will have enough time and feedback and will be able to turn in a high-quality project, we require you to follow the following milestones:
Turn in your final deliverables by placing them in a single ZIP file (not to exceed 500GB), uploading it to a private folder (e.g., Google Drive or Box), and sharing a link with your instructor(s) no later than this deadline. Your final deliverables must include the following items:
It is extremely important to start working on your project as early as possible in the semester, or you are unlikely to finish in time. You can always reach out to, or meet up with, the instructor if you have questions or concerns about your project progress throughout the semester.
Lecture Times: TuTh 1:30-3:30 PM
Lecture Room: Beyster 1690
Lectures Dates: Sep 4, 2018-Dec 11, 2018
Office Hours: (By appointments only) 4769 Beyster Building
Presentation Practice Schedule: Student presentors must meet the instructor in his office the Wednesday before the week in which they will present at these times: 5:00-5:40 PM for student(s) presenting the following Tuesday, and 5:40-6:20 PM for student(s) presenting the following Thursday. Note: if you cannot make it, you must notify the instructor at least 48 hours before your appointment so that it can be rescheduled.
Presentation Submission Deadline: Student presenters must email the final copy of their slides (both PPTX and PDF) to both the GSI and the instructor no later than 10AM of the morning of their presentation date. If your presentation contains animations, it is your responsibility to ensure that the generated PDF is still readable.
Presentation Template: Please use this template.
Max Number of Missed/Skipped Lectures: You may skip up to 2 lectures due to legitimate reasons.
Review Submission Deadline: By 8:59 PM each Monday you must submit your reviews for all the papers that will be discussed during that week. For the first week's papers, the submission deadline is 8:59 PM of the day before day the paper is going to be presented.
Review Grading Deadline: Once you receive an email from the instructors assigning you to grading the reviews for a particular paper, you have a week to complete the task and email the grades back to the instructor who will in turn (periodically) upload them to Canvas. The detailed instructions will be sent to you via email.
How to Read Other Students' Reviews: You can see other students' reviews only after its submission deadline has passed by following this link. If the deadline has passed and you still do not see the reviews for a particular paper, simply try and submit a dummy review for that paper. This will automatically publish the submitted reviews of that paper.
Midterm Time & Location: The midterm will be held 5-7pm on Oct 23, 2018 in room EECS1200.
Team Size Policy: You must form a team with 1 or 2 other students from the class. One-person teams and teams of larger than 3 are disallowed. Exceptioanlly, 4 students per team are also allowed with the instructor's explicit permission. However, note that the project contribution is expected to be proportional to the number of students in the team.
Initial Project Idea Submission Deadline: Bring in a hard-copy draft (1-2 pages long; word or PDF format) to the lecture on Sep 20, 2018.
Final Project Proposal Submission Deadline: Email your final project proposal (1-3 pages long; word or PDF format) to the instructor by 11pm Oct 4, 2018.
Final Project Posters/Demos: The final project poster/demo session will be held on Dec 11 during regular class hours. Location TBD.
Final Deliverables Submission Deadlines: You must submit your final project deliverables by noon on Dec 12, 2018. See the instructions here.
Grading: The following table summarizes the breakdown of your overall grade.
Paper Presentation: 15%
Each student will be assigned to present at least one paper during the semester. Presentations will be graded on a scale of 0-3 as follows:
Class Participation: 5%
Your participation grade will be based on a qualitative assessment of the value of your contributions in leading and participating in class discussions throughout the semester.
Paper Reviews: 15%
Each student is expected to read and write a review for each of the mandatory readings (see here for details). Each paper review is graded on a scale of 0-3 as follows:
Midterm Exam: 25%
The midterm will be a closed-book exam.
Final Project: 40%
Your >project grade will be based primarily on your poster presentation and final derliverables. Students in the same team may receive different grades depending on their contributions, i.e., students contributing equally to the project will receive equal grades.
Disabilities: Students with documented disabilities (including invisible disabilities) are encouraged to contact the instructor during the first three weeks of the semester.