Lizette Zietsman's Home Page
Fall 2018: (to appear)
Current interests involve the development and analysis of numerical methods for solving optimal control problems where the dynamics are described by partial differential equations; for example, fundamental fluid flows. This includes applications such as the design, optimization and control of energy efficient buildings.
These numerical challenges include computational algorithms for the optimal placement of sensors and actuators that maximize observability and controllability. In addition, the discretization of the optimal control problem leads to extremely large systems of finite dimensional Riccati equations. In order to generate practical algorithms, we take advantage of the underlying infinite dimensional partial differential equation structure. This includes studying the sensitivity of the algebraic Riccati equation, mesh-independence of Newton methods used to solve the Riccati equation, as well as the use of adaptive methods to compute the optimal feedback gain. Furthermore, in designing numerical methods for control problems, special attention should be paid to properties that will guarantee that the approximation scheme yield strong convergence of the operators. The approximation method used in the generating the Riccati equation must also be selected to ensure that the finite dimensional equations are well conditioned and additional features like mesh-independence are obtained.
The Society for Industrial and Applied Mathematics (SIAM) has a guide to careers in Applied Mathematics and a page Careers & Jobs with career information resources. (Note that we also have a SIAM Student Chapter on campus.)
The American Mathematical Society's page "Mathematical Sciences Career Information" has career profiles and other interesting information about nonacademic employment.