Pei-Gen Ye
Papers
2
Total Citations
26
H-Index
2
About
Pei-Gen Ye is a rising researcher at the forefront of artificial intelligence and distributed systems security. His work primarily spans two critical, high-impact domains: the security and privacy of Deep Reinforcement Learning (DRL), and secure, real-time computation in edge networks. Ye’s most significant contribution is his comprehensive survey on security and privacy issues in DRL, which has rapidly accumulated 22 citations since 2024. This work systematically maps the threat landscape for DRL agents—from adversarial attacks to privacy leakage—and provides a crucial taxonomy of countermeasures, serving as an essential reference for researchers building robust AI systems. In parallel, Ye addresses the practical challenges of modern information systems through his work on EdgeStreaming, which tackles the problem of enabling secure, real-time analytics on resource-constrained devices like security cameras and mobile robots. By proposing a framework for distributed edge intelligence, he bridges the gap between low-end hardware and the demand for accurate, low-latency data processing. Ye’s research is particularly notable for its dual focus: advancing foundational AI security while simultaneously solving pressing engineering problems in edge computing, making his work highly relevant for both academic researchers and industry practitioners.
Research Focus
Key Achievements
Top Papers
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