Our faculty in this area work on a number of themes, including Numerical Analysis, Inverse Problems, Computational Science and Engineering, and the application of mathematical and computational tools to problems in Biology and Medicine. Research in these directions actively involves faculty as well as graduate and undergraduate students, with regular informal meetings and seminars and the Schlumberger-Tufts Computational and Applied Mathematics Seminar. Our work is highly interdisciplinary, with collaborations within the broader Tufts community, the many universities in the Boston area, and worldwide.James Adler's expertise is in the study of complex fluids, including computational plasma physics and magnetohydrodynamics. Bruce Boghosian's work currently focuses on the study of fluid dynamics, particularly using lattice Boltzmann methods. Christoph Börgers studies differential equations models in neuroscience, and their computational solution. Misha Kilmer's work is in the area of numerical linear algebra and inverse problems, as well as in multilinear algebra. Xiaozhe Hu focuses on adaptive, parallel, and multilevel methods for partial differential equations and graph problems such as multiphase flow in porous media and magnetohydrodynamics. Todd Quinto uses microlocal analysis to understand inverse problems and develop and improve his tomography algorithms. Our graduate students are closely involved in all aspects of this research. James Murphy leverages methods of applied harmonic analysis, machine learning, and nonparametric statistics to develop new algorithms and analyze large, high-dimensional datasets. Alex Hening uses stochastic processes, random dynamical systems and ODE/PDE to study models from mathematical ecology.