Research on improving System-on-Chip (SoC) security through novel architectures and design flows while balancing other system requirements
Investigating robustness and trustworthiness of AI-enhanced systems in applications such as code generation, physical chip design, and image processing
Studying model vulnerabilities and defenses under adversarial and non-adversarial conditions, including backdoor poisoning and adversarial perturbations
Working on hardware security problems including hardware Trojan detection, IP protection against reverse engineering, and side-channel attacks
Exploring how advances in AI/ML impact the landscape of hardware security