Michael Yuhas is a Postdoctoral Researcher at the SCOPE Lab whose work focuses on out-of-distribution detection, deep learning, and their applications to embedded systems and smart grid infrastructure. His research addresses the critical challenge of ensuring that AI systems can recognize when they encounter situations outside their training distribution — a key requirement for safe deployment in real-world cyber-physical systems.
Michael’s expertise in deep learning and embedded systems contributes to the lab’s efforts in building robust AI decision procedures for energy systems and other societal-scale infrastructure, where reliable detection of anomalous or out-of-distribution conditions is essential for maintaining system safety and performance.