My research centers on developing machine learning and statistical physics frameworks for analyzing the dynamics of complex systems—more specifically ice deformation fields. I currently work on methods for learning dynamics from noisy and discontinuous radar imagery and developing graph learning-based approaches for large-scale discrete element models. I also explore concepts from statistical physics present in ice dynamics (multifractality, renormalization group, self-organized criticality) with the goal of linking engineering-scale ice mechanics to geophysical scale statistical behavior and uncovering scale-dependent structures and critical behavior. I am interested other related research topics across diverse application domains.