# Computational Science & Numerical Analysis

Computational science is a key area related to physical mathematics. The problems of interest in physical mathematics often require computations for their resolution. Conversely, the development of efficient computational algorithms often requires an understanding of the basic properties of the solutions to the equations to be solved numerically. For example, the development of methods for the solution of hyperbolic equations (e.g. shock capturing methods in, say, gas-dynamics) has been characterized by a very close interaction between theoretical, computational, experimental scientists, and engineers.

## Faculty

Laurent Demanet
*Applied analysis, Scientific Computing*

Alan Edelman
*Parallel Computing, Numerical Linear Algebra, Random Matrices*

Steven Johnson
*Waves, PDEs, Scientific Computing*

Gilbert Strang
*Numerical Analysis, Partial Differential Equations*

## Instructors & Postdocs

Peter Baddoo
*Fluid Dynamics, Complex Analysis, Machine Learning*

Keaton Burns
*PDEs, Spectral Methods, Fluid Dynamics*

Pui Tung Choi
*Applied and Computational Geometry, Metamaterials, Quantitative Biology, Medical Imaging*

Andrew Horning
*Numerical Analysis, Scientific Computing, Large-Scale And Infinite-Dimensional Spectral Problems*

Adam Kay
*Hydrodynamic Quantum Analogues*

RaphaĆ«l Pestourie
*Inverse design in nanophotonics, efficient approximate solvers in optics, deep surrogate for PDES.*

Adrien Scheuer
*Multiscale modeling, model order reduction, scientific machine learning *

## Graduate Students*

Mo Chen
*Optimization, Scientific Computing*

Sarah Greer
*Imaging, inversion, signal processing*

Sung Woo Jeong
*Numerical Linear Algebra, Random Matrix Theory*

George Stepaniants
*Statistical Learning of PDEs, Continuous Neural Networks*

*Only a partial list of graduate students