Guang Zhao

Guang's primary research interests are artificial intelligence, machine learning, and AI-driven scientific discovery, with a particular focus on foundation models, Bayesian optimization, and adaptive learning. More specifically, his research investigates how to develop efficient, generalizable, and data-driven AI methodologies to address complex scientific and engineering challenges. His current research focuses on developing scientific foundation models and integrating them with AI reasoning to advance scientific discovery and decision-making.