Our research group interests are mainly focused on the numerical methods for PDEs using spectral/pseudospectral methods, radial basis function methods, discontinuous Galerkin discretizations, uncertainty quantification, and reduced basis methods.
Our group is interested in different aspects of theoretical and computational gravitational physics.
Our research group studies ways in which students at all levels, K-20, can engage more deeply with mathematical thinking through computational approaches. We seek to understand how students and teachers respond to serious mathematical and scientific questions that involve extensive computation, and what sorts of computational investigations are feasible for students at different stages of development.
Data science is an interdisciplinary research effort in data-intensive methodologies and applications. Research focuses on data collection, analysis, and visualization in diverse application areas. Some of these areas include artificial intelligence, autonomous mobile robotics, nursing informatics, bioinformatics, and scientific data management and reproducibility.