Research in data science in the Department of Mathematics & Computer Science focuses on the design, analysis, and application of computational algorithms for data-centric problems arising in diverse domains. For example, statistical, machine-learning, and linear programming approaches are developed and applied for prediction, classification, regression, and clustering. Linear and non-linear models and hybrid meta-heuristics are explored for data analytics. The following faculty are involved in data science-related research: Haiyan Cai, Yuefeng Wu, Adrian Clingher.
Algebra, Geometry and Topology
Faculty in this group focus on algebraic geometry, group theory, topology and string theory. Adrian Clingher does research on string theory, moduli spaces, K3 surfaces and Calabi-Yau manifolds. Prabhakar Rao and Ravindra Girivaru do research on algebraic vector bundles, hypersurfaces and varieties in projective spaces.
Faculty in this group, including Qingtang Jiang are active researchers in Computational Harmonic Analysis, Computer-aided Geometric Design, and Approximation Theory, with emphasis on the theory and methods of Multivariate Splines and Wavelets. They are also members of the Institute of Computational Harmonic Analysis which is an integrated unit of the department.
Probability and Statistics
Research in Probability and Statistics in the Department of Mathematics and Computer Science is focused on theoretical as well as on the computational aspects of these disciplines. Haiyan Cai conducts research in Statistics and Probability with focus in the areas of statistical modeling, statistical computations, spatial statistics, Markov random fields, and their applications. Yuefeng Wu conducts research in Bayes data analysis, non-parametric method, and inference on dynamic system.