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).