Welcome to the data-driven mechanics research group!
The goal of our group is to develop and utilize data-driven computational frameworks to characterize, understand, model and control the multi-scale material systems and their associated uncertainties. We are a highly interdisciplinary group with expertise in Machine learning, Mechanics and Materials. The research topics include but not limited to Deep Learning, Nueral Operators, Uncertainty Quantification, Generative Models, Plasticity, Fracture, Metals, Composites, and Mechanical Meta-Materials. The impact of our work lies in defense and protection, sustainable energy, mechanical/civil/aerospace structures, among others.
