About the group
The Khasawneh group is interested in enhanced modeling and
characterization of dynamical systems using numerical and
analytical methods. The effectiveness of these models is
evaluated and improved through comparisons with observed system
behavior. The group's work includes investigating:
nonlinear dynamics
Numerical & experimental
The lab investigates challenging topics in the broad area of dynamical systems.
Application areas include delay differential equations,
parameter identification, and stochastic systems.
time series analysis
Revisiting state-of-the-art
This project presents a novel approach for studying dynamical systems in their parameter space
by examining their time series based on the underlying topological descriptors.
machine learning
Learning on new spaces
This project seeks to formulate the foundations of machine learning when the important features of a
dynamical system are summarized by descriptors generated with topological data analysis (TDA).