The goal of this project is to provide a scientific basis to understand and leverage the interaction among physical systems, artificial intelligence/cyber-human agents and their environment through the development of control synthesis tools to reason about safety and security under real-world uncertainties. Such cyber-physical systems, which include many vital infrastructures that sustain modern society (e.g., transportation systems, electric power distribution) are usually safety-critical. If compromised, serious harm to the controlled physical entities and the people operating or utilizing them as well as significant economic losses can result. However, model mismatches between the real system and an imperfect model of the system, in addition to other sources of uncertainties (e.g., measurement errors) disable existing safety and security protection, while robust solutions without learning may be overly conservative. These challenges demonstrate the need to design novel computational tools that can guarantee robust safety and security of cyber-physical systems under real-world uncertainties without sacrificing performance. The project includes research activities that are integrated with education and outreach to engage students and industry partners to appreciate the importance of safety and security for computing-related technologies.