On the trail with my favorite co-authors-in-training.

I am an Assistant Professor of Strategic Management and Entrepreneurship at the Carlson School of Management, University of Minnesota – Twin Cities.

My research examines how transformative technologies — artificial intelligence and digitalized platform markets — reshape the way firms hire and organize labor. The prevailing view is that these technologies lower hiring costs, conferring an advantage on the firms best able to use them. My research complicates this view. Across a series of papers, I show that these technologies reshape hiring and evaluation in unintended ways, redistributing costs rather than reducing them, and that the benefits they offer are not uniformly available. The technologies now mediating hiring do not automate away the advantage firms gain through the people they hire; they relocate it — to a different stage of the hiring process, to a different party in the exchange, or to a different level of the firm.

I organize my work into two streams. The first asks what these technologies do to hiring and evaluation. Whether the mechanism is a search filter, an information rule, an algorithmic recommendation, or AI assistance inside a hierarchy, the costs of finding, evaluating, and organizing workers do not disappear. They move — from screening to the job offer, from the employer to the platform, and from the bottom of a hierarchy to the experts at its top. The second stream takes the technology as given and asks who captures value from it. Here the advantage is contingent rather than inherent: it belongs to firms that protect their independence from the platform, to workers with better access to information about opportunities, and to buyers who can appropriate the value of what AI produces. A third, more recent line of work turns hiring itself into a measure, using firms’ technical job postings to observe where they are investing at the scientific frontier.

My work is primarily empirical and pays careful attention to causal identification, drawing on field experiments, regression discontinuity designs, and granular administrative data that captures the complete hiring funnel across thousands of firms. It has been published in Management Science, the Strategic Management Journal, the Journal of Labor Economics, Organization Science, and Strategy Science.

To stay close to how technology is changing labor markets in practice, I spent the summer of 2025 as a visiting senior data scientist at Indeed.com, studying how employers trade off among machine learning algorithms, filters, and Boolean search when locating and hiring workers. While completing my doctorate, I worked as a staff economist on the data science team at oDesk (now Upwork).

Before joining Carlson, I was a Visiting Assistant Professor of Strategy at Georgetown’s McDonough School of Business. I received my Ph.D. in Business Administration from UC Berkeley’s Haas School of Business, and hold an M.B.A. and a B.S. in Mechanical Engineering from Washington University in St. Louis. Earlier in my career I worked as an economic consultant at Chicago Partners and Navigant Consulting.