320A Clark Hall
Research Areas Shape analysis Image analysis Riemannian and discrete geometry

Nicolas Charon’s innovative mathematical research on shape and image analysis for medical imaging and computational anatomy is helping to frame the new field of computational medicine.

An assistant research professor of applied mathematics and statistics, Charon develops mathematical and numerical models for the representation, registration, and statistical analysis of geometric structures occurring in the anatomy and in biology. His research has innovative applications to the modeling and analysis of the shape of curves and surfaces extracted from medical images, in particular. He is also interested in the interplay between anatomy and function in datasets that combine geometry with additional measured signals such as response to stimuli or tissue thickness. Charon is creating new analysis tools to adequately model and estimate joint variabilities in shape and function.

He also works in developing computational methods to compress and accelerate the vast amounts of data generated by diffusion MRI (dMRI), an imaging protocol that retrieves the diffusion patterns within the brain and is key to understanding its connectivity. His work will provide researchers and clinicians new computational tools for fast reconstruction and analysis of diffusion data.

Charon co-developed two MATLAB software libraries to assist researchers in different shape analysis tasks:  fshapesTk and h2metrics. He joined Johns Hopkins University in 2015 and is a core member of the Hopkins Institute of Computational Medicine and the Center for Imaging Science.

His conference leadership includes organization of several mini symposiums at the 2016 and 2018 Society for Industrial and Applied Mathematics (SIAM) Conference on Imaging Sciences and the 2017 SIAM annual meeting. Charon is a regular reviewer for numerous journals such as The SIAM Journal of Imaging Sciences, International Journal of Computer Vision, and the Journal of Foundations of Computational Mathematics.

He received his BS in Mathematics (2007), MS (2009) in Applied Mathematics & Image Processing, and PhD  (2013) in Applied Mathematics from ENS Cachan in Paris. He was also a postdoctoral researcher at the  University of Copenhagen’s Computer Science department.