My primary research interest is in machine learning, with a focus on deep learning for structured data. Specifically, I study how to apply deep learning techniques to sets, graphs, point clouds, surfaces, weight spaces and other data types that have an inherent symmetry structure. My goal is twofold: first, to understand and design deep learning architectures from a theoretical perspective, for example, by analyzing their expressive power; and second, to demonstrate their practical effectiveness on real-world problems involving structured data.