

Computational Methods for Estimation in the Presence of Uncertainty



By Professor H. Thomas Banks
ABSTRACT:
In numerous applications in the biological and engineering sciences, one
encounters inverse problems where the uncertainty and/or variability in
parameters and mechanisms to be modeled are a fundamental part of the
problem formulation. This is in addition to the datadriven uncertainty
that arises naturally in most inverse problems. We discuss several classes
of modeling formulations and associated computational methodologies in the
context of examples arising in materials and biological processes drawn
from the Industrial Applied Mathematics Program at N.C.State University.
Both theoretical and computational findings will be presented.



