about

My research studies the commercialization of scientific innovations, the diffusion of technologies into markets, and the role of AI in shaping how these are identified and evaluated at early stages for development.

Prior to academia, I founded a startup providing software and machine-learning translation solutions for enterprise clients. I also spent years in M&A, where I led numerous projects in technological sectors such as advanced water treatment technologies, biotech, energy generation, and materials science.

I will be on the job market during the 2025-2026 academic year.

published papers

• Measuring the Commercial Potential of Science with Wesley Cohen and Sharique Hasan paper | data | code Strategic Management Journal, 2025, Articles in Advance. NBER Working Paper 32262 Abstract

  We develop an ex-ante measure of commercial potential of science, an otherwise unobservable variable driving the performance of innovation-intensive firms. To do so, we rely on LLMs and neural networks to predict whether scientific articles will influence firms' use of science. Incorporating time-varying models and the quantification of uncertainty, the measure is validated through both traditional methods and out-of-sample exercises, leveraging a major university’s technology transfer data. To illustrate the methodological contributions of our measure, we apply it to examining the impact of university reputation and university privatization of science, finding that firms’ reliance on reputation may lead to foregone opportunities, and privatization (i.e., patenting) appears to increase firms’ use of the science of one university. We make our measure and method available to researchers.

working papers

• Science, Startups, and the Problem of Value Capture: Thin Acquisition Markets, Weak Outside Options Abstract

  Science-based innovations increasingly rely on startups to reach the market. Yet, in critical sectors such as energy, industrials, and materials, entrepreneurial activity remains limited. This paper investigates whether limited value capture at exit constrains these ventures. I estimate value creation and capture in startup acquisitions by combining acquisition prices with acquirer stock returns, adjusting for market noise to isolate the economic signal attributable to the acquisition. Science-based startups capture 46 cents per dollar of acquisition-induced surplus, compared to 61 cents for non-science startups—a 25% penalty. Conversely, they create 20% more joint surplus, consistent with continued entry despite the capture gap. To explain these patterns, I examine a central mechanism: the structure of a startup’s exit conditions. I argue that science-based startups face thinner, more concentrated acquisition markets and limited ability to scale independently. These features weaken the startup’s bargaining power and constrain value capture. Indeed, I find that science-based startups face up to 40% fewer potential acquirers, who are 53% larger on average, and that their value capture is more sensitive to buyer concentration. Concentrated markets have a dual effect: large incumbents enable greater surplus creation, but also shift bargaining power away from startups, allowing acquirers to extract most of the gains from innovation. Finally, I find that the capture gap disappears when startups can scale commercialization independently. The results indicate that constrained exit environments limit returns to science-based entrepreneurship, highlighting the importance of competitive acquisition markets, markets for technologies, and alternative commercialization pathways in incentivizing upstream innovation.

• Taste Before Production: The Role of Judgment in Entrepreneurial Idea Generation with Ronnie Chatterji, Sharique Hasan, and Rick Larrick paper Abstract

  Crafting high-quality ideas is crucial for entrepreneurs to succeed, yet evidence about the factors that shape the idea-generation process is scarce. A long-standing question is whether differences across entrepreneurs in market judgment—the ability to evaluate business ideas—explain differences in ideas’ quality and composition. We conduct an experiment with an intervention that improves subjects’ ability to evaluate an idea’s market potential, finding that improved judgment leads subjects to generate ideas 15% higher in quality and more complete, with stronger effects among initially poorly-calibrated subjects. Our results support a potential mechanism: individuals with developed judgment mentally test more ideas and better filter them before committing to one. Simple training can improve judgment and idea quality, complementing ex-post, experimental methods by reducing the costs of testing ideas.

• Predicting Market Impact in Biomedical Research: General vs. Domain-Specific Modelswith Wesley Cohen and Sharique Hasan
• When Do Intermediaries Distort Scientific Diffusion? Evidence from Google Searchwith Wesley Cohen and Sharique Hasan

works in progress

• Breadth, Depth, and the Market Paths of Innovations
• Commercializing Deep Tech: Understanding Frictions to University Invention Disclosure with Ramana Nanda, Elena Novelli, and Markus Perkman
• Markets for Capabilities: How Manufacturing and Distribution Platforms Incentivize Entry in Energy Technologies with Jay Prakash Nagar
• The Realization Gap: Untapped Research with Commercial Potential with Wesley Cohen, Sharique Hasan, and Yeqing Liu
• Acquisitions Do Create Value: A Measurement Reassessment