Social and Decision Analytics

Cesar Montalvo

  • Research Assistant Professor
Cesar Montalvo headshot
Contact

Bio

Cesar Montalvo is a Research Assistant Professor with the Social and Decision Analytics Division of the Biocomplexity Institute and Initiative. He works at the interface of mathematical models, economics, statistics, and public policy. Cesar has a master’s degree in economics from Iowa State University. He received his Ph.D. in Applied Mathematics for Life and Social Sciences from Arizona State University. His dissertation focused on dynamical systems regarding social mobility. He currently works on projects regarding food insecurity, health metrics, the skilled technical workforce, and social mobility at the community level.

In the past, he served as a Coordinator of Information at the Office of the President in Ecuador, advising the president on education, health, infrastructure, and natural resources. He also worked as Director of Research at the Ministry of Production. Cesar has taught micro and macroeconomics and rural development classes in the United States, the Czech Republic, and Ecuador. He has also mentored students at the Mathematical Theoretical Biology Institute at Arizona State University and the Data Science for the Public Good program at the University of Virginia.

Cesar is driven by a strong desire to conduct research and practice that reduces poverty and inequality in communities.

CV

    • Dynamical Systems
    • Health Economics
    • Political Economy
    • Statistical Models
    • Higher Education and Social Mobility
    • Macroeconomics
    • Social Contagion Models
    • Epidemiology

  • Ph.D. in Applied Mathematics for Life and Social Sciences, Arizona State University School of Human Evolution and Social Change

    M.S. in Agricultural and International Economics, Iowa State University

    B.A. Finance and Economics, Universidad San Francisco de Quito - Quito, Ecuador

Past Project

Skilled Technical Workforce

We are working with the National Center of Science and Engineering Statistics to address this gap. By discovering nontraditional data sources and using them to describe and quantify the skills and non-degree credentials that can lead to STW jobs, we can help policymakers and educators address an urgent problem and empower job seekers to make informed decisions about their future.
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Official Statistics
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