I'm a Postdoctoral Fellow at Georgia Tech with interests in general relativity, nonlinear dynamics, periodic orbit theory, numerical methods, symmetry in physics, and model discovery.
My goal is to enable other scientists to discover simple governing equations directly from their data. I am always happy to help, so get in touch if you have interesting data.
Links of interest are my main SPIDER repository, my fast sparse regression algorithm SPRINT, and my general purpose iterative matrix solver block-GMRES for high-dimensional systems of equations.
I have a YouTube channel that I post on occasionally.
(in review) Scalable Sparse Regression for Model Discovery: The Fast Lane to Insight
(in review) Scalable Discovery of Fundamental Physical Laws: Learning Magnetohydrodynamics from 3D Turbulence Data
Data-driven Discovery of the equations of Turbulent Convection
Covariant Guiding Center Equations for Charged Particle Motions in General Relativistic Spacetimes
Learning fluid physics from highly turbulent data using sparse physics-informed discovery of empirical relations (SPIDER)
Physically informed data-driven modeling of active nematics
PhD (Physics) Georgia Institute of Technology 2019-2023
MS (Physics) Georgia Institute of Technology 2018-2019
BS (Physics/Mathematics) Ohio Northern University 2014-2017
matthew.golden (at) gatech.edu
Office 2410
Klaus Advanced Computing Building