Tel: (585) 752-5832
I am a fifth-year PhD candidate in Finance at Simon Business School, University of Rochester. My research focuses on empirical corporate finance. Specifically, I'm interested in:
- Entrepreneurship, Artificial Intelligence, Innovation, VC/PE, and M&As.
For my current research projects, I was awarded the 2018 Kauffman Knowledge Challenge Grant.
I will be available for interviews at the upcoming AFA meetings in San Diego, CA.
- 2019 Financial Management Association European Doctoral Student Consortium
- Selected Media Coverage: UoR Newscenter
I identify a specific channel (the prospect of getting funded or acquired by large firms) through which entrepreneurship is affected. By exploiting the variation across entrepreneurs' reactions to the two announcements of Amazon's new headquarters (HQ2) search, I find that after the announcement of the 20 finalist cities, new startups that are the potential funding or acquisition targets of Amazon are more likely to be established in one of those 20 cities. After the winning cities were selected, the newly created potential targets of Amazon are more likely to be founded only in the winning cities but not in the losing finalist cities. I also find that there exists a local competition for startups to get funded or acquired by Amazon, which is inconsistent with agglomeration explanation. I present evidence consistent with two possible underlying mechanisms: the synergy benefits from selling out to large firms and the difficulty in obtaining early-stage funding from non-corporate investors.
- Selected Media Coverage: The New York Times, The Wall Street Journal, Inside Higher ED, Tencent News, Communications of the ACM, policy.ai, TechTalks
- Presented at 2019 Stanford HAI-AI Index Roundtable Workshop on Measurement in AI Policy: Opportunities and Challenges
- Included in the 2019 Stanford AI Index Report.
- The data for our AI Brain Drain Index can be downloaded here.
Human capital is essential to AI-driven innovation. The scarcity of the human capital needed for AI R&D created an unprecedented brain drain of AI professors from North American universities into the industry between 2004 and 2018. We provide a causal evidence that AI faculty departures from universities reduced the creation of startups by students who then graduated from these universities. On the intensive margin, these departures also reduce the early-stage funding graduates' startups receive. The disruption in the knowledge transfer from professors to students emerges as the main channel for the negative effect of the human capital reallocation for innovation.
This paper investigates the spillover effects of private equity (PE) buyouts on innovation of the targets' public industry rivals. Using patent-based metrics, I find a robust positive effect of PE buyouts on innovation outcomes of the targets' industry peers and direct competitors. Moreover, I argue that the positive effect is causal by constructing an instrumental variable as a proxy for PE firms' industry experience and focus. Finally, I present evidence that PE buyouts affect industry innovation likely through forcing the targets' rivals to become more focused.