College - Author 1
College of Engineering
Department - Author 1
Computer Science Department
Advisor
Pheonix Fang, College of Engineering, Computer Science and Software Engineering Department
Funding Source
This research was funded by Cal Poly's Academic Affairs Office
Date
10-2025
Abstract/Summary
The objective of this SURP proposal is to investigate machine unlearning as a viable approach to support the right to be forgotten in artificial intelligence (AI) systems, many of which rely heavily on personal data. The capability to selectively remove user-specific information upon request—without necessitating full model retraining—is critical for safeguarding individual privacy and enhancing computational and energy efficiency. This project will undertake a systematic review of state-of-the-art unlearning techniques, evaluate their performance using standard benchmark datasets, and assess their feasibility in real-world applications. In addition, the project will provide participating students with practical experience in implementing and analyzing machine unlearning methods. The outcomes will include a comparative analysis of different approaches and the development of recommendations for improving the effectiveness and efficiency of unlearning in privacy-sensitive AI systems.
October 1, 2025.
Included in
URL: https://digitalcommons.calpoly.edu/ceng_surp/124