Ruixuan Wang
Papers
1
Total Citations
8
H-Index
1
About
Dr. Ruixuan Wang is a leading researcher at the intersection of artificial intelligence security and brain-inspired computing. His work primarily focuses on understanding and mitigating vulnerabilities in emerging machine learning paradigms, particularly hyperdimensional computing (HDC) and deep neural networks. Dr. Wang’s major contributions include pioneering the study of adversarial attacks on HDC, as demonstrated in his highly cited work "PoisonHD: Poison Attack on Brain-Inspired Hyperdimensional Computing" (2022, 8 citations), which revealed critical security flaws in this energy-efficient alternative to traditional deep learning. By exposing how subtle data manipulations can compromise HDC systems, his research has been instrumental in guiding the development of more robust and trustworthy AI architectures. Beyond security, Dr. Wang’s investigations into the computational demands of deep neural networks have highlighted the trade-offs between performance and efficiency, influencing the design of lightweight models for resource-constrained environments. His work is widely recognized for bridging the gap between theoretical vulnerability analysis and practical defense mechanisms, making him a key voice in the ongoing effort to build safer, more resilient AI systems for real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1PoisonHD: Poison Attack on Brain-Inspired Hyperdimensional Computing8 citations · 2022