CS294: RISE Course — Real-time, Intelligent, and Secure Execution


This seminar aims to serve as a catalyst for research in the RISE lab, the new lab following the AMPLab. We will read and discuss papers on the state-of-the-art of learning systems (large-scale model training, deep learning, real-time robust inference), big data systems (scale-out vs scale-up, scalable data analytics), and systems security (computation on encrypted data, secure hardware enclaves, language-based mechanisms). Because this is a research class we have capped the enrollment at 30 students.

An important component of the class will be the final project aiming at original research in this space. In addition, students will be required to present several papers throughout the year. We expect students to attend every lecture and actively participate in conversation about the papers.

The course website for this class is being hosted on GitHub pages. If you see any errors or omissions or would like to contribute content or suggested reading to any of the discussion topics please consider emailing us or sending a pull request to this GitHub repository.