AMS strives to achieve excellence in the development and application of statistical and mathematical methods. Our focus is on modeling of the world around us (we are methodologists who like to develop new methods in the process of solving real-world problems). In our research, we use a wide variety of approaches, ranging from computationally intensive numerical solutions of systems of partial differential equations to qualitative methods in the performance analysis of distributed algorithms, and passing by Markov chain Monte Carlo methods and other techniques for approximating high-dimensional integrals.

AMS specializes in various research areas including:

  • Mathematical modeling, including dynamical systems, mathematical biology, fluid dynamics, control theory and uncertainty quantification, with applications to astrophysics, biology, engineering, and geophysics;
  • Bayesian nonparametric methods, Bayesian inference, prediction, and decision-making with applications to bioinformatics, computational biology, machine learning, visualization and the environment.

These areas of expertise are described in more detail here

We are committed to full interdisciplinary collaborations in which we work together with investigators from other fields, so that our publications are a mix of methodology articles in leading AM and S journals and substantive articles in leading journals in the fields in which we collaborate. Some current partners and funding sources inlcude NASA Ames, Los Alamos National Laboratory, Lawrence Livermore National Laboratories, the National Center for Atmospheric Research (NCAR) and the National Marine Fisheries Service (NMFS) Santa Cruz Laboratory.