Computational and applied mathematicians model phenomena from a wide variety of science and engineering disciplines and design computer algorithms to solve the resulting mathematical problems. Faculty at Michigan Tech study problems from fluid dynamics, model polymers and multiphase flows, simulate optical phenomena, and study composite materials. Several faculty focus on the design and analysis of numerical methods for solving partial differential equations.

## Faculty and Areas of Interests

Computational fluid dynamics; Simulation and modeling of multi-phase and viscoelastic fluids; Drop dynamics in emulsions and sprays

Inverse problems in partial differential equations; Numerical optimization; Mathematical software

Applied mathematics; Online and hybrid (online/classroom) education

Turbulence Modeling, Computational Fluid dynamics; High-accuracy numerical methods for PDEs; Uncertainty Quantification, high-dimensional integration

Composites Modeling

Scientific computing; Numerical PDEs; Parallel Computing; Plasma modeling and simulation; Dimension Reduction

Numerical Analysis and Scientific Computing; Numerical PDEs; Radial Basis Functions Method; Fractional Differential Equations

Algorithms that can be parallelized on GPUs; Applications of differential equations to science and engineering

Numerical Methods for PDEs; Inverse Problems; Scientific Computing; EM methods in Geophysics

Computational fluid dynamics, especially the modeling of sprays and multiphase flows

Numerical PDE, Scientific computing; Computational modeling of Nafion material; Mathematical image processing, inverse problems, nonlinear optics

Superconvergence of discontinuous Galerkin methods; Numerical cosmology; Numerical methods for two-phase flow in porous media; Numerical methods for partial differential equations with blow-up solutions