This individual is an Associate Professor specializing in uncertainty quantification, scientific machine learning, and stochastic optimization for civil engineering systems. With a multidisciplinary background in civil and electrical engineering, their research focuses on physics-informed machine learning, infrastructure resilience, and high-dimensional computational methods. They have developed innovative approaches for seismic reliability analysis and sparse polynomial chaos expansions, published in leading journals. Their teaching spans systems engineering, machine learning applications in civil engineering, and sustainable infrastructure. Prior to their current role, they held postdoctoral positions at USC and the University of Utah, bringing interdisciplinary expertise to complex engineering challenges.