Adrianna Gillman's research focuses on developing efficient, accurate and robust numerical methods for approximating solutions to partial differential equations. The algorithms she develops allows users to simulate physical phenomena on a desktop computer that is regularly shipped out to super computer. Her research specialties include scattering, imaging, and fluid simulations.
keywords
numerical linear algebra, numerical partial differential equations, integral equations, high order discretizations
APPM 1360  Calculus 2 for Engineers
Primary Instructor

Spring 2020
Continuation of APPM 1350. Focuses on applications of the definite integral, methods of integration, improper integrals, Taylor's theorem, and infinite series. Degree credit not granted for this course and MATH 2300.
APPM 4600  Numerical Methods and Scientific Computing
Primary Instructor

Fall 2022
Provides an introduction to numerical analysis and scientific computing. Numerical analysis topics include root finding, interpolation, quadrature, linear system solution techniques, and techniques for approximating eigenvalues. Scientific computing topics include code development and repository management in addition to an introduction to shared and distributed memory computing. Involves handson learning with weekly group interactions and a final project including a report and inclass presentation. Recommended prerequisite: knowledge of a programming language such as Python, and C++.
APPM 4610  Numerical Differential Equations
Primary Instructor

Spring 2023
Provides an introduction to the most commonly used techniques for numerically solving boundary value problems and time dependent problems and the corresponding linear systems. Topics include finite difference methods, the finite element method, the spectral method, spectral collocation methods, Euler and RungeKutta methods. Scientific computing skills such as advanced code and memory management will be developed. Involves handson learning with weekly group interactions and a final project. Department enforced prerequisite: Knowledge of a programming language such as Python, and C++ is required.
APPM 4650  Intermediate Numerical Analysis 1
Primary Instructor

Fall 2019 / Fall 2021
Focuses on numerical solution of nonlinear equations, interpolation, methods in numerical integration, numerical solution of linear systems, and matrix eigenvalue problems. Stresses significant computer applications and software. Department enforced prerequisite: knowledge of a programming language. Same as MATH 4650.
APPM 4660  Intermediate Numerical Analysis 2
Primary Instructor

Spring 2021 / Spring 2022
Continuation of APPM 4650. Examines numerical solution of initialvalue problems and twopoint boundaryvalue problems for ordinary differential equations. Also looks at numerical methods for solving partial differential equations. Department enforced prerequisite: knowledge of a programming language. Same as MATH 4660.
APPM 5600  Numerical Analysis 1
Primary Instructor

Fall 2020 / Fall 2021
Solution of nonlinear algebraic equations, interpolation, integration, approximation, and numerical linear algebra. Department enforced prerequisite: APPM 3310 or MATH 2130 and experience with a scientific programming language.
MATH 4650  Intermediate Numerical Analysis 1
Primary Instructor

Fall 2019 / Fall 2021
Focuses on numerical solution of nonlinear equations, interpolation, methods in numerical integration, numerical solution of linear systems, and matrix eigenvalue problems. Stresses significant computer applications and software. Department enforced restriction: knowledge of a programming language. Same as APPM 4650.
MATH 4660  Intermediate Numerical Analysis 2
Primary Instructor

Spring 2021
Continuation of MATH 4650. Examines numerical solution of initialvalue problems and twopoint boundaryvalue problems for ordinary differential equations. Also looks at numerical methods for solving partial differential equations. Same as APPM 4660.
MATH 5600  Numerical Analysis 1
Primary Instructor

Fall 2020
Solution of nonlinear algebraic equations, interpolation, approximation theory and numerical integration. Department enforced prerequisites: MATH 2130 or MATH 2135 or APPM 3310 and experience with a scientific programming language. Instructor consent required for undergraduates.