May 6, 2020
- Christos Makridis | Digital Fellow
Digital Fellow
Christos is a Research Assistant Professor at the W. P. Carey School of Business in Arizona State University, a Digital Fellow at MIT IDE (Sloan School of Management), a Non-resident Fellow at the Kennedy School of Government in Harvard University, and a Non-resident Fellow at the Institute for Religious Studies in Baylor University.
Christos also serves as a Senior Adviser with Gallup and a Senior Policy Adviser with the United States National Artificial Intelligence Institute in the Department of Veteran Affairs. Christos earned his doctorates in Management Science and Engineering and Economics at Stanford University and his undergraduates in Economics and Mathematics at Arizona State University.
Makridis’ research focuses in the areas of labor & organizational economics, the digital economy & cybersecurity, and household finance with a driving commitment to understanding how individuals and firms respond to large-scale change, particularly social and technological. In particular, how do individuals, as well as firms, learn and adapt amid change? How do incentives affect the returns to human capital formation, and how do these decisions in turn shape long-run outcomes? What role, and in what circumstances, does public policy play in either advancing or stifling these goals? These are a cross-section of the research questions at the top of my mind. Here is his SSRN page with research papers.
Makridis also actively works with organizations, both government and non-government, on overlapping areas of research interest and on organizational decision-making that require the integration of data and strategy. His prior work experience includes serving on the White House Council of Economic Advisers, focusing on cybersecurity, technology, and space activities, together with management consulting and entrepreneurship, including an ongoing startup called Hyperthesis where he serves as the Director of Academic Engagement and Economics Research. Hyperthesis has developed a machine learning based algorithm for processing vast amounts of text, specifically from research articles, to help organizational decision-makers understand the latest research in an accessible and visual form. Our aspiration is to empower employees in organizations to make more data-driven decisions.
May 6, 2020
May 6, 2020
April 7, 2020