02-Nov Midterm Project Presentations on 15th Nov. Details here
02-Nov Dr. Karthikeyan Shanmugam from IBM Research confirmed as our fourth guest speaker
02-Oct Project proposal presentations on 6 Oct
29-Sep First group discussion on "Robustness challenges in real-world AI deployment" on 4 Oct. Details here
26-Sep Dr. Joseph Whittaker confirmed as our third guest speaker
01-Sep Jason Ditman and Derek Puzcz (General Motors) and Prof. Karthik Pattabiraman (UBC) confirmed as guest speakers.
10-Aug Webpage Up!
Course Description
Traditional dependability and interpretability techniques are no longer viable for ML and AI driven applications. Such applications are prone to (i) existing dependability issues such as software/hardware failures and bugs, (ii) uncertainty in the data (both training and operational/inference data) leading to biases and corner-case inference failures, and (iii) uncertainty in the machine learning models and their composition with other ML models or the rest of the system. This course will cover advanced research topics for designing dependable and interpretable ML/AI systems, especially focusing on the safety, security, reliability and trustworthy aspects of the emerging applications. We will draw inspiration from emerging safety-critical AI applications such as self-driving ground and aerial vehicles (e.g., Waymo’s self-driving cars or Boeing’s autonomous systems), health applications such as medical assistants (e.g., IBM Watson) and surgical robots (e.g., RAVEN II), and ML-driven computer systems (e.g., UIUC’s Symphony).
The class will consist of lectures, with the intent of building up common knowledge and grounding and then transition to discussion of both seminal and recent research papers that outline new challenges and opportunities in designing and validating dependable AI systems. Additionally, the course will include:
- Guest lectures from industry and academia
- Student-led presentations
- Group discussions
- A project focused on resilience assessment and design
More details here
- Class Timings: Mon/Wed 11:00am - 12:20pm (CT) via Zoom. Live lectures and discussion.
- Zoom link : https://illinois.zoom.us/j/84232534530
- Zoom password: Through invitation (or Piazza)
- Paper discussions and class announcements will be made on Piazza. Students should enroll in the “ECE 598RKI Dependable AI Systems” course.
- Homeworks, presentations and project materials should be submitted on Canvas.
- Signup Deadlines: Presentation (Friday, 27 Aug), Project (end of week 4)
- Evaluation: Details here
- Academic Accommodation: DRES requirements must be reported to instructor/TA by the end of 1st week (8/27/2020)
Team
| Instructor | Teaching Assistant |
|---|---|
| Ravishankar K. Iyer | Anirudh Choudhary |
 |
 |
| Office Hours: Online (via Zoom); 12:30pm - 1:30pm Monday | Office Hours: Online (via Zoom), 12:30pm - 1:30pm Wednesday |
| Email: rkiyer@illinois.edu | Email: ac67@illinois.edu |
Academic Integrity Policy
The University of Illinois at Urbana-Champaign Student Code should also be considered as a part of this syllabus. Students should pay particular attention to Article 1, Part 4: Academic Integrity. Read the Code at the following URL: http://studentcode.illinois.edu/.
Academic dishonesty may result in a failing grade. Every student is expected to review and abide by the Academic Integrity Policy: http://studentcode.illinois.edu/. Ignorance is not an excuse for any academic dishonesty. It is your responsibility to read this policy to avoid any misunderstanding. Do not hesitate to ask the instructor(s) if you are ever in doubt about what constitutes plagiarism, cheating, or any other breach of academic integrity.