Ari Stern

Ari Stern is a Professor of Mathematics at Washington University in St. Louis, specializing in Geometric Numerical Analysis. His work bridges geometry, applied analysis, and computational mathematics, focusing on numerical methods that maintain global accuracy for differential equations through modern geometric principles.

He earned his B.A. and M.A. in Mathematics from Columbia University and a Ph.D. in Applied and Computational Mathematics from Caltech (2009), advised by Jerrold E. Marsden and Mathieu Desbrun. Prior to WashU (2012), he was a postdoc at UCSD with Michael Holst.

• Research Interests: Geometric integration, finite element exterior calculus, symplectic geometry, and applications to physics and machine learning.

His recent publications address multisymplecticity, functional equivariance, and hybrid finite element methods. Collaborations span topics from Alzheimer’s disease modeling via machine learning to Hamiltonian mechanics and geometric electrodynamics.

• Awards: NSF Grant (2019).

• Teaching: Courses include Numerical Methods for Differential Equations, Measure Theory, and Honors Mathematics.