Our group is involved in the two seemingly disparate research directions of computational plasma physics and agent-based modeling. In both cases, we employ computational methods for interacting many-body systems to understand the collective dynamics of the systems we study. More and more, machine learning plays a role in everything we do.

In computational plasma physics, we are interested in modeling a wide range of plasmas, from ultracold neutral plasmas through non-equilibrium warm dense matter to hot dense plasmas. Much of our current work focuses on understanding hydrodynamics and transport in strongly coupled Coulomb systems, with applications to the basic statistical mechanics of closures in such systems, and on the modeling of inertially confined fusion plasmas. The tools we use to address these challenges include analytical/numerical modeling, kinetic theory, hydrodynamics, and molecular dynamics. In particular, our group is interested in combining these methods to create new multiscale methods. For more detailed information, please click on the links to the right. We currently have openings for students and postdocs in these areas of computational physics.

We are interested in using agent-based models to study a variety of systems. For example, we are currently using agent-based models to study influenza outbreaks. Infectious disease dynamics are inherently multiscale, and computational models of infectious diseases face similar challenges. We are modeling influenza pandemics using agent-based models that allow “microscopic” information (viral dynamics at the cellular level) to influence “macroscopic” dynamics at the global population scale. Our goals are to use multiscale models to understand infectious disease outbreaks at large scales, to optimize the selection of mitigation strategies, to understand the emergence of drug resistance, and to develop nowcasting capabilities for epidemics and pandemics. For more detailed information, please click on the links to the right. We currently have openings for students and postdocs in these research areas.