Yufeng Yao (姚雨锋)
Yufeng Yao (姚雨锋)
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I am a PhD candidate and Early Career Academic Fellow in Finance at the University of New South Wales (UNSW) in Sydney, Australia. My research interests include corporate innovation, machine learning in finance, corporate finance, corporate governance, entrepreneurial finance, and venture capital. I will be on the 2025-26 academic job market.
Contact Information:
344D, Level 3,
UNSW Business School,
Sydney, NSW 2052, Australia
Working Papers
Working Papers
Scientists on Corporate Boards: An Alternative Mechanism for Accessing Scientific Knowledge
with Ronald W. Masulis
Presentations: EFA (2025), FIRS (2025), Global Entrepreneurship and Innovation Research Conference (2025), Baltic Economic Conference (2025), Norwegian School of Economics Corporate Finance Conference (2025), FMA (2025, Scheduled)
Abstract: As US firms dramatically cut internal scientific research, undermining their absorptive capacity for scientific knowledge, we identify scientists on corporate boards (BdScis) as an alternative mechanism for accessing basic scientific research. Surprisingly, 70% of BdScis are industry and government scientists, while only 30% are university-affiliated. Firms with BdScis demonstrate superior commercialization of scientific research, producing patents of higher quality. We document two mechanisms that help explain their contributions: (1) their scientific expertise measured by both patent-to-publication citations and their recent scientific publications gives them valuable insights that can help guide corporate innovation; (2) their professional networks can benefit firms seeking talented inventors. We address endogeneity using local BdSci supply as an instrument and the Human Genome Project as an exogenous shock.
with Roham Rezaei
Presentations: SFS Cavalcade North America (2025), AFA (2025), Columbia Private Equity Research (2025), ABFER (2025), ACFOW (2024), FOM Dartmouth College (2024), EUROFIDAI-ESSEC Paris December Finance Meeting (2024), UNSW
Abstract: Basic science R&D can deter investors due to coordination and appropriability frictions. We study whether a coordinated public funding—supplying basic science as a public good—fosters VC investment. Our quasi-natural experiment is the BRAIN Initiative (BI), a big science program aimed at mapping the human brain. Using machine learning, we first find large spillover effects of BI in neurotech. Our difference-in-differences analysis shows that BI raised the probability of receiving VC, led to larger funding rounds at higher valuations, and resulted in more successful VC exits for neurotech startups. The BI's spillovers explain these results: (1) an expanded supply of skilled academic labor, (2) increased innovation activity and (3) deeper integration with complementary technologies like AI and big data. Our findings suggest that public science institutions supply an essential public good for private investment in innovation.
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