My research focuses on the incentives and institutions that drive science and innovation. I use administrative data from fields like structural biology and astronomy to investigate academic competition and scientific careers. I also study the labor market for scientists and inventors, trying to better understand how we identify, train, and promote future innovators. I graduated with a PhD in economics from the Massachusetts Institute of Technology in 2020 and earned a BS in economics, mathematics, and political science from Brigham Young University in 2014.

• PhD, 2020, Economics, Massachusetts Institute of Technology
• BS, 2014, Economics, Mathematics, and Political Science, Brigham Young University, Magna Cum Laude

• Assistant Professor, Economics, Brigham Young University, 2021-2022
• Postdoctoral Researcher, Strategy, Kellogg School of Management, Northwestern University, 2020-2021

Technology and Innovation ll (MECS-549-2)
This course establishes fundamental ways in which ideas differ from other goods, then uses these concepts to evaluate the origins of innovation, economic growth, firm dynamics, entrepreneurship, innovation clusters, and the diffusion of new technology. The course substantially reviews core empirical literature, including methods and data sets that are suited to studying ideas and innovation.

Innovation Economics and the Science of Science (MECS-548-0)
Innovation touches many fields, including virtually all fields of economics -- whether economic growth, industrial organization, labor economics, health, finance, trade, or urban economics. As such, the course provides important foundations for PhD students in economics across many sub-disciplines, as well as students studying innovation strategy, organizational behavior, creativity, entrepreneurship, and science policy from different disciplinary perspectives. In tandem with theoretical approaches, this course substantially reviews core empirical literature, including empirical methods and an expanding set of remarkable data sets that are suited to studying ideas and innovation. This PhD course also provides an inroad to the growing field of the “science of science,” which emphasizes the use of high-scale data, network methods, and machine learning, together with more traditional econometric approaches, to understand the science and innovation process and implications for society.”

Technology and Innovation Strategy (STRT-463-0)
This course develops approaches to analyzing strategies within technology markets. It teaches students how to analyze technology markets, where firm structure, product cycles and competitive environment change rapidly. The course offers tools to analyzing both entrepreneurial and corporate innovation strategy. These issues are illustrated through general readings and with cases from computing, electronics, online, communication, and transportation markets. The course strikes a balance between presenting a few general models of market behavior and presenting a few key episodes of market behavior. It is aimed at three types of students: those who anticipate taking management positions in technology-intensive firms where they must formulate strategy, those who anticipate investing in technology markets and must analyze firm strategy, and those who anticipate contracting with firms that do much of their business in these types of markets. Discussion questions, individual assignment, and final exam.