Nicolas Charon

Nicolas Charon is an Assistant Professor in the Department of Mathematics at the University of Houston. He holds a PhD in Mathematics from École normale supérieure de Cachan (2013) and completed postdoctoral research at the University of Copenhagen. His research focuses on geometric methods for medical imaging and computational anatomy, including diffeomorphic registration, functional shape analysis, and Riemannian metrics on curves/surfaces. He has been supported by the NSF DMS-1945224 CAREER Award and has developed software tools like fshapesTk, h2metrics, and ShapeGraph_H2match.

Key research areas include varifold-based shape registration, metamorphoses of functional shapes, and sparse methods for diffusion MRI compression. Charon has advised three PhD students and contributed to over 50 publications. His work bridges theoretical mathematics with applications in healthcare, including stroke risk assessment via left atrial appendage morphology analysis and 4D human shape synthesis.

Recent projects involve scalable frameworks for PDE solution operators, self-supervised learning of human body scans, and data-driven elastic shape analysis with topological constraints. Charon’s interdisciplinary approach integrates geometry, optimization, and machine learning to advance computational anatomy and medical imaging technologies.