Mark Wilkinson is a Mechanical Engineering PhD student at Purdue University whose research spans scientific machine learning, finite elements, and nonlinear solid mechanics.

He develops Bayesian inverse methods for extracting material properties from complex biomechanical data, with an emphasis on integrating physics and computation. His current interests include applying group-theoretic principles to scientific ML models to ensure symmetry-preserving structure.