Selected Research

We design an uncertainty quantification measure for active learning of dynamical systems with the Koopman operator.

We develop a learning framework for modeling the global dynamics of complex dynamical systems using Koopman operator theory and Fourier Features.

We leverage the mobility of autonomous surface vehicles to better understand river health, flow and sediment dynamics, and the potential impacts climate change may have on riverine environments.

A novel robotic platform is being developed to localize and classify novel agricultural sensors that directly interface crop surfaces to assess crop conditions.