Papers
1
Total Citations
5
H-Index
1
About
Dr. Yuqun Zhang is a leading researcher in the security and reliability of GPU-accelerated autonomous embedded systems, with a particular focus on memory isolation and leakage resilience. Their most cited work, "gGuard: Enabling Leakage-Resilient Memory Isolation in GPU-accelerated Autonomous Embedded Systems" (2021), addresses a critical vulnerability in systems like robotics and autonomous vehicles, where GPUs serve as performance co-processors. Dr. Zhang identified that existing GPU hardware and software—including device drivers, compilers, and operating systems—lack robust mechanisms to prevent memory leakage between processes, posing significant security risks. By developing gGuard, they introduced a novel framework that enforces strong memory isolation without sacrificing performance, directly enhancing the safety of real-time autonomous operations. This contribution has garnered 5 citations, reflecting its foundational role in an emerging field. Dr. Zhang’s work bridges the gap between embedded systems security and GPU architecture, offering practical solutions for next-generation autonomous platforms. Their research continues to influence both academic studies and industrial implementations, making them a key figure in advancing trustworthy AI-driven systems.
Research Focus
Key Achievements
Top Papers
- 1