Federico Girosi is a senior economist at RAND. He has extensive experience in the areas of health economics, simulation modeling, health services research and Artificial Intelligence. He is currently working on several simulation projects designed to estimate the benefits and costs of health policy interventions at both the federal and state levels. These projects focus on expanding insurance coverage and improving health care access, with a particular emphasis on low income populations and immigrants. He is one of the developers of the RAND COMPARE microsimulation model for the analysis of health care reform. Girosi is also currently involved in a project that utilizes Electronic Health Records to estimate costs to the California county mental health system under improved care scenarios, and has recently performed work on the application of machine learning to the generation of syntehtic data sets. Girosi has also worked on projects that estimated the costs and benefits of preventive health in the U.S. and of improved access to diagnostic tools in the developing world. Previously, Girosi was an academic at Western Sydney University (Sydney, Austalia), working with government organizations and the private sector on applied problems at the intersection of data science and health services research. Before joining RAND, he spent 10 years at MIT working on the foundations of machine learning and applications of machine learning to computer vision. Girosi received his Ph.D. in health policy from Harvard University and his Ph.D in physics from the University of Genova.
Ph.D. in health policy, Harvard University; Ph.D. in physics, University of Genova; Ph.D. in health policy, Harvard University; Ph.D. in physics, University of Genova
