My research has consistently centered on computational models of interacting systems. I began with computer graphics, simulation, and agent-based models of group behavior, then moved toward information diffusion and influence in online social systems. During my doctoral work at the University of Central Florida, I studied how local behavioral rules and network structure shape the spread of information, while contributing to large-scale DARPA research on social simulation and influence pathways.

My current work asks the inverse question: when we observe the behavior of a complex system, what can we actually infer about the mechanisms that generated it? I approach this problem using agent-based modeling, machine learning, conformal prediction, network science, and statistical methods. Across these areas, I am particularly interested in methods that are both scientifically interpretable and computationally usable.