The Group

The goal of our lab is to design, rigorously analyze and efficiently implement novel algorithms for computer simulation of complex physical, engineering and biological systems. The underlying mathematical models often take the form of nonlinear partial differential equations. We develop numerical methods such as finite difference, finite volume and finite element methods for approximating these PDEs in a robust and efficient manner. More recently, we design state-of-the-art uncertainty quantification (UQ) and Machine Learning (ML) algorithms for data-driven simulations of these complex systems