Fernando Alarid-Escudero, Ph.D., is an Assistant Professor of 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, and was an Assistant Professor at the Center for Research and Teaching in Economics (CIDE) Región Centro, Aguascalientes, Mexico, from 2018 to 2022, prior to coming to Stanford. His research focuses on developing statistical and decision-analytic models to identify optimal prevention, control, and treatment policies to address a wide range of public health problems and develops novel methods to quantify the value of future research. Dr. Alarid-Escudero is part of the Cancer Intervention and Surveillance Modeling Network (CISNET), a consortium of NCI-sponsored investigators that includes modeling to improve our understanding of the impact of cancer control interventions (e.g., prevention, screening, and treatment) on population trends in incidence and mortality. Dr. Alarid-Escudero co-founded the Stanford-CIDE Coronavirus Simulation Modeling (SC-COSMO) workgroup (https://www.sc-cosmo.org). He also co-founded the Decision Analysis in R for Technologies in Health (DARTH) workgroup (http://darthworkgroup.com) and the Collaborative Network on Value of Information (ConVOI; https://www.convoi-group.org), international and multi-institutional collaborative efforts where we develop transparent and open-source solutions to implement decision analysis and quantify the value of potential future investigation for health policy analysis. He received a BSc in Biomedical Engineering from the Metropolitan Autonomous University in Iztapalapa (UAM-I), and a Master’s in Economics from CIDE, both in Mexico.