The STAR Lab develops systems-theoretic foundations and engineering methodologies for artificial intelligence systems operating in complex and adaptive environments. The lab studies learning-enabled systems as components of larger architectures embedded in feedback with their environments. Research areas include resilient AI systems, cyber-physical system resilience, adaptive autonomy, and decision systems under uncertainty and adversarial interaction. By combining systems engineering and machine learning, the STAR Lab aims to design AI technologies that remain stable, governable, and resilient in real-world deployment.
Research Areas
Artificial Intelligence and Machine Learning
Computational Sciences
Engineering, Robotics, and Physical Sciences
Theory, Foundations, and Advanced Methodologies
Faculty
