CS 598AWG: Machine Learning for Systems

Fall 2022

Aishwarya Ganesan
pronouns: she/her/hers

When? Tue/Thu 3:30 pm-4:45 pm
Where? 1043 Sidney Lu Mechanical Engineering Building (location)

Office Hours
When? Fridays 2-3pm and by appointment
Where? 3120 SC

Who? Sarthak Moorjani
Office hours:
12:30-1:30 on Tuesdays (tentative), location: TBD

Course Description

In the past decade, machine learning has transformed many applications including image and speech recognition, machine translation, and game playing. Recently machine learning has also been transforming the way we build computer systems. For example, fundamental mechanisms in computer systems such as indexing, scheduling, query processing, and caching are being replaced by learned components. This course will explore such recent advancements in using ML techniques for building systems. We will cover a variety of topics where machine learning or deep learning techniques have been employed such as:

  • Index structures
  • Distributed KV stores
  • Concurrency control
  • Caching
  • Scheduling and resource management
  • Congestion control
  • SSDs and storage
  • Operating systems
  • Video streaming and storage

We will first read a few papers on state-of-the-art approaches in these topics. Then, we will discuss learning-based approaches to these problems and compare the two.

The course will be based on two pillars:

  • Reading papers: There is no text and most (if not all) classes will be based on research papers. We will read and review two papers each week from systems, databases, and networking conferences. The reading load will be somewhat heavy (two to four papers each week). Before each class, students are expected to read the assigned papers, and submit a review of the paper.
  • Doing a research project: Students will also form a small team (2-3 members) to do a sizable research project. A good project involves exploring a new idea or conducting an in-depth study, and could potentially be published in a good systems workshop or conference. I will help you choose ideas and present your results.


An undergraduate course in one of:

  • operating systems (CS 423)
  • distributed systems (CS 425)
  • databases (CS 411)
  • computer networks (CS 438)
Only a preliminary background in machine learning is needed.


  • Class participation: 10%
  • Review: 15%
  • Paper presentation: 15%
  • Project proposal: 10%
  • Project checkpoint: 15%
  • Final project presentation + report: 35%
There will be no exams in this course :)

Please feel free to raise any issue or concern with the instructor. The instructor is here to help you succeed in this course.

  • Academic Integrity

Academic dishonesty may result in a failing grade. Every student is expected to review and abide by the Academic Integrity Policy: https://studentcode.illinois.edu/article1/part4/1-401/. Do not hesitate to ask the instructor if you are ever in doubt about what constitutes plagiarism, cheating, or any other breach of academic integrity.

  • Statement on anti-racism and inclusivity

The intent of this section is to raise student and instructor awareness of the ongoing threat of bias and racism and of the need to take personal responsibility in creating an inclusive learning environment.

The Grainger College of Engineering is committed to the creation of an anti-racist, inclusive community that welcomes diversity along a number of dimensions, including, but not limited to, race, ethnicity and national origins, gender and gender identity, sexuality, disability status, class, age, or religious beliefs. The College recognizes that we are learning together in the midst of the Black Lives Matter movement, that Black, Hispanic, and Indigenous voices and contributions have largely either been excluded from, or not recognized in, science and engineering, and that both overt racism and micro-aggressions threaten the well-being of our students and our university community.

The effectiveness of this course is dependent upon each of us to create a safe and encouraging learning environment that allows for the open exchange of ideas while also ensuring equitable opportunities and respect for all of us. Everyone is expected to help establish and maintain an environment where students, staff, and faculty can contribute without fear of personal ridicule, or intolerant or offensive language. If you witness or experience racism, discrimination, micro-aggressions, or other offensive behavior, you are encouraged to bring this to the attention of the course director if you feel comfortable. You can also report these behaviors to the Bias Assessment and Response Team (BART) (https://bart.illinois.edu/). Based on your report, BART members will follow up and reach out to students to make sure they have the support they need to be healthy and safe. If the reported behavior also violates university policy, staff in the Office for Student Conflict Resolution may respond as well and will take appropriate action.

  • Statement on CS CARES and CS Values and Code of Conduct

CS Values and Code of Conduct. The CS CARES Committee is available to serve as a resource to help people who are concerned about or experience a potential violation of the Code. If you experience such issues, please contact the CS CARES Committee. The instructors of this course are also available for issues related to this class.

  • Statement on Mental Health

Diminished mental health, including significant stress, mood changes, excessive worry, substance/alcohol abuse, or problems with eating and/or sleeping can interfere with optimal academic performance, social development, and emotional well-being. The University of Illinois offers a variety of confidential services including individual and group counseling, crisis intervention, psychiatric services, and specialized screenings at no additional cost. If you or someone you know experiences any of the above mental health concerns, it is strongly encouraged to contact or visit any of the University's resources provided below. Getting help is a smart and courageous thing to do -- for yourself and for those who care about you.

Counseling Center: 217-333-3704, 610 East John Street Champaign, IL 61820

McKinley Health Center:217-333-2700, 1109 South Lincoln Avenue, Urbana, Illinois 61801

University wellness center: https://wellness.illinois.edu/

  • Students with Disabilities

To obtain disability-related academic adjustments and/or auxiliary aids, students with disabilities must contact the course instructor as soon as possible and provide the instructor with a Letter of Academic Accommodations from Disability Resources and Educational Services (DRES). To ensure that disability-related concerns are properly addressed from the beginning, students with disabilities who require assistance to participate in this class should apply for services with DRES and see the instructor as soon as possible. If you need accommodations for any sort of disability, please speak to me after class, or make an appointment to see me or see me during my office hours. DRES provides students with academic accommodations, access, and support services. To contact DRES, you may visit 1207 S. Oak St., Champaign, call 217-333-1970, e-mail disability@illinois.edu or visit the DRES website at http://www.disability.illinois.edu/. Here is the direct link to apply for services at DRES, https://www.disability.illinois.edu/applying-services