At the IDEAS Lab, our research interests include design automation for intelligent cyber-physical systems (CPS) and Internet-of-Things (IoT) applications, safe, robust and data-efficient machine learning for embodied AI systems, cyber-physical security, and energy-efficient CPS. Our recent projects have been focusing on the cross-layer design, verification, and adaptation of learning-enabled cyber-physical systems (LE-CPS), particularly addressing the safety, robustness, security, energy, and data challenges in utilizing deep neural networks for CPS and in operating CPS within dynamic and uncertain environment. We work on applications in the domains of connected and autonomous vehicles, smart buildings and infrastructures, robotics, advanced manufacturing, IoT, etc.