Skip to main content
King Abdullah University of Science and Technology
Computer, Electrical and Mathematical Sciences and Engineering
CEMSE
Computer, Electrical and Mathematical Sciences and Engineering
  • Home
  • Study
    • Prospective Students
    • Current Students
    • Internship Opportunities
  • Research
    • Research Overview
    • Research Areas
    • Research Groups
  • Programs
    • Applied Mathematics and Computational Science
    • Computer Science
    • Electrical and Computer Engineering
    • Statistics
  • People
    • All People
    • Faculty
    • Affiliate Faculty
    • Instructional Faculty
    • Research Scientists
    • Research Staff
    • Postdoctoral Fellows
    • Students
    • Alumni
    • Administrative Staff
  • News
  • Events
  • About
    • Who We Are
    • Leadership Team
  • Apply

Data Privacy

Provable and Measurable Machine Unlearning in Modern Learning Systems

Cheng-Long Wang, Ph.D. Student, Computer Science
Mar 10, 10:30 - 12:30

B2 L5 R5209

Machine Unlearning Data Privacy Trustworthy AI Federated learning machine learning AI

This dissertation examines the foundations of machine unlearning under realistic learning system constraints and proposes both theoretically grounded unlearning algorithms and principled evaluation frameworks for modern learning systems.

Cheng-Long Wang

Ph.D. Student, Computer Science

Machine Unlearning Data Privacy Trustworthy AI Federated learning

Cheng-Long Wang is a PhD candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), advised by Prof. Di Wang.

Computer, Electrical and Mathematical Sciences and Engineering (CEMSE)

Connect with us

Footer

  • A-Z Directory
    • All Content
    • Announcements
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice