I am an Associate Engineer at RAND, a research organization dedicated to improving policy and decision-making through research and analysis.

My research uses simulation models and (high-performance) computing to inform public policy when decision-makers face complex dilemmas and there is no obvious policy choice due to uncertainty or conflicting societal objectives. I have a background in engineering and a Ph.D. in Policy Analysis.

I self-identify as an eclectic modeler - someone who has been trained on, appreciates, and uses a wide variety of modeling paradigms. Whether you self-identify as an econometrician, biostatistician, systems dynamicist, or complex systems modeler, we have a lot to chat about. I believe that all models are wrong, but all models can be useful if used by competent and honest researchers.

My recent research investigates COVID-19 control strategies and informs the design of pandemic response plans. I also work on other health policy areas, such as cancer early detection.

More generally, I am interested in using computational models to shed light on tradeoffs imposed by policy problems. A recent example of this involves using many-objective optimization to investigate the effects of policies to reduce racial wealth disparities.

If you’re interested in my work and want to connect, follow me on Twitter and connect on LinkedIn!