Cheng-Long Wang
Cheng-Long Wang is a PhD candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), advised by Prof. Di Wang.
Biography
Cheng-Long Wang is a PhD candidate in Computer Science (CS) at King Abdullah University of Science and Technology (KAUST), advised by Prof. Di Wang. His research focuses on machine unlearning, privacy-preserving machine learning, and trustworthy AI systems. His work explores both theoretical foundations and system-level design for provable and measurable machine unlearning in modern learning frameworks, including graph learning, federated learning, and large-scale deep models.
Research Interests
Cheng-Long Wang's research focuses on machine unlearning, privacy-preserving machine learning, and trustworthy AI systems. His work explores both theoretical foundations and system-level design for provable and measurable machine unlearning in modern learning frameworks, including graph learning, federated learning, and large-scale deep models.
Awards and Distinctions
- USENIX Security ’25 Student Grant, USENIX Association, 2025
- EPFL - SURI Fellowship, EPFL, 2024
- CEMSE Dean's List Award, KAUST, 2023
- USENIX Security '23 Student Grant, USENIX Association, 2023
Education
- Master of Science (M.S.)
- Computer Science, Northwestern Polytechnical University, China, 2021
- Bachelor of Engineering (B.Eng.)
- Control Systems and Automation, Northwestern Polytechnical University, China, 2018
Related People
Academic Advisors
Di Wang
- Assistant Professor, Computer Science