Research

Data Science for Social Justice

Reduced-Order Modeling

Spatiotemporal dynamical systems are ubiquitous across all areas of science and engineering. While some systems of interest can be studied through first-principles governing equations, often, the underlying dynamics are unknown. Furthermore, even for problems where equations are known, analytical solutions are rare. Computational solutions are then plagued by issues of nonlinearity, multiple relevant scales of time and space, chaos, and high-dimensionality. When parametric studies are needed, these simulations become prohibitively expensive, even under the most advance computational architectures.

Other Work