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Fernando Alarid-Escudero is an Assistant Professor in Health Policy at Stanford University School of Medicine. He obtained his Ph.D. in Health Decision Sciences from the University of Minnesota School of Public Health. His research focuses on developing statistical decision-analytic models to identify optimal prevention, control, and treatment policies while conducting cost-effectiveness analyses to address a wide range of public health problems. He has developed novel methods to quantify the value of future research. Alarid-Escudero is a member of the Cancer Intervention Surveillance Modeling Network (CISNET) consortium, which includes a group of investigators sponsored by the National Cancer Institute in the U.S. He utilizes simulation modeling to evaluate the impact of cancer control interventions on population trends in incidence and mortality. Additionally, he co-founded the Decision Analysis in R Technologies for Health (DARTH) workgroup and the Collaborative Network on Value Information (ConVOI), which are both international multi-institutional efforts to develop transparent and open-source solutions for implementing decision analysis in health policy analysis. He holds a B.Sc. in Biomedical Engineering from the Metropolitan Autonomous University Iztapalapa and a Master's in Economics from CIDE in Mexico.
Stanford University • Stanford, CA
Teaching and conducting research in health policy.
The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.